Permutation-based content encryption with manifests in a content centric network

Information

  • Patent Grant
  • 10305865
  • Patent Number
    10,305,865
  • Date Filed
    Tuesday, June 21, 2016
    8 years ago
  • Date Issued
    Tuesday, May 28, 2019
    5 years ago
Abstract
One embodiment provides a system that facilitates encryption of manifest content based on permutation. During operation, the system partitions, by a computer system, a collection of data into a first set of content objects, wherein a content object is a chunk comprised of a plurality of bytes. The system performs a first permutation function on the first set of content objects to obtain a first set of permuted content objects. The system creates a manifest based on the permuted content objects, wherein a manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest. The system encodes the first permutation function and the permuted content objects in the manifest, thereby facilitating an authorized entity that receives the manifest to reassemble the manifest contents based on the permutation function.
Description
RELATED APPLICATION

The subject matter of this application is related to the subject matter in the following applications:

    • U.S. patent application Ser. No. 13/847,814, entitled “ORDERED-ELEMENT NAMING FOR NAME-BASED PACKET FORWARDING,” by inventor Ignacio Solis, filed 20 Mar. 2013 (hereinafter “U.S. patent application Ser. No. 13/847,814”);
    • U.S. patent application Ser. No. 12/338,175, entitled “CONTROLLING THE SPREAD OF INTERESTS AND CONTENT IN A CONTENT CENTRIC NETWORK,” by inventors Van L. Jacobson and Diana K. Smetters, filed 18 Dec. 2008 (hereinafter “U.S. patent application Ser. No. 12/338,175”); and
    • U.S. patent application Ser. No. 14/231,515, entitled “AGGREGATE SIGNING OF DATA IN CONTENT CENTRIC NETWORKING,” by inventors Ersin Uzun, Marc E. Mosko, Michael F. Plass, and Glenn C. Scott, filed 31 Mar. 2014 (hereinafter “U.S. patent application Ser. No. 14/231,515”);


      the disclosures of which are herein incorporated by reference in their entirety.


BACKGROUND
Field

This disclosure is generally related to distribution of digital content. More specifically, this disclosure is related to a method and system for facilitating random access to a piece of content in a content centric network.


Related Art

The proliferation of the Internet and e-commerce continues to create a vast amount of digital content. Content-centric network (CCN) architectures have been designed to facilitate accessing and processing such digital content. A CCN includes entities, or nodes, such as network clients, forwarders (e.g., routers), and content producers, which communicate with each other by sending interest packets for various content items and receiving content object packets in return. CCN interests and content objects are identified by their unique names, which are typically hierarchically structured variable length identifiers (HSVLI). An HSVLI can include contiguous name components ordered from a most general level to a most specific level. CCN is an effective network architecture for delivering content.


A manifest is a CCN content object that can be used to encode a larger “original” content object by including pointers or links to other “member” or “children” content objects (e.g., leaves) that contain the data that make up the larger content object encoded by the manifest. Because a manifest is itself a content object, a manifest can include links or children pointers to data objects (e.g., leaf nodes) or other manifests (e.g., non-leaf nodes). In order to reassemble the original content object encoded by a manifest, a consumer or client computing device typically performs an in-order traversal of the manifest tree, by concatenating bytes from the leaf nodes to form the whole original content object. If the original content object is encrypted, the manifest can specify the decryption metadata (i.e., the keys) to be used for all member content objects to which the manifest points. The consumer must locate or obtain these decryption keys before reassembling the content object, which can involve decrypting each member content object in the manifest. However, decrypting each member content object in the manifest may involve computationally costly procedures and may also induce significant delays.


SUMMARY

One embodiment provides a system that facilitates encryption of manifest content based on permutation. During operation, the system partitions, by a computer system, a collection of data into a first set of content objects, wherein a content object of the first set is a chunk comprised of a plurality of bytes. The system performs a first permutation function on the first set of content objects to obtain a first set of permuted content objects. The system creates a manifest based on the permuted content objects, wherein a manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest. The system encodes the first permutation function and the permuted content objects in the manifest, thereby facilitating an authorized entity that receives the manifest to reassemble the manifest contents based on the permutation function.


In some embodiments, the first permutation function is performed on one or more of: bytes comprising an ordered concatenation of the chunks of the first set; bytes comprising each chunk of the first set; and each chunk of the partitioned collection of data, wherein the bytes comprising a respective chunk are not permuted.


In some embodiments, the manifest indicates the second set of content objects based on a direct embedding of a respective content object or a child pointer to a respective content object.


In some embodiments, encoding the first permutation function in the manifest is based on an order of child pointers which correspond to each permuted content object of the first set, and encoding the permuted content objects in the manifest is based on a tree-like topology.


In some embodiments, the system performs a second permutation function on an order of child pointers which correspond to content objects indicated in the manifest. The system encodes the second permutation function in the manifest.


In some embodiments, the first permutation function is based on one or more of: shuffling the bytes comprising the first set of content objects; Lehmer codes; a symmetric block cipher; an encryption algorithm; and a form of permutation encoding.


In some embodiments, encoding the first permutation function in the manifest is based on one or more of: embedding in the manifest the first permutation function by including the first permutation function in decryption metadata associated with the manifest; including in the manifest a link to retrieve the first permutation function, wherein a successful retrieval of the first permutation function via the included link involves a verification of authentication information; and indicating a secure channel over which to retrieve the first permutation function.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 illustrates an exemplary computing environment that facilitates encryption of manifest content based on permutation, in accordance with an embodiment of the present invention.



FIG. 2A presents an exemplary manifest tree illustrating partitioned collections of data, in accordance with an embodiment of the present invention.



FIG. 2B presents an exemplary manifest with child content object chunks, including a whole-content permutation function performed on the concatenated bytes of a partitioned collection of data, in accordance with an embodiment of the present invention.



FIG. 2C presents an exemplary manifest with child content object chunks, including a whole-chunk permutation function performed on the bytes of each chunk of a partitioned collection of data, in accordance with an embodiment of the present invention.



FIG. 2D presents an exemplary manifest with child content object chunks, which illustrates the numbered chunks of a partitioned collection of data before a chunk-level permutation function is performed on the numbered chunks, in accordance with an embodiment of the present invention.



FIG. 2E presents an exemplary manifest with child content object chunks corresponding to FIG. 2D, including a chunk-level permutation function performed on the numbered chunks, in accordance with an embodiment of the present invention.



FIG. 2F presents an exemplary manifest with child content object chunks, which illustrates the numbered chunks of a partitioned collection of data before a traversal permutation function is performed on the numbered chunks, in accordance with an embodiment of the present invention.



FIG. 2G presents an exemplary manifest with child content object chunks corresponding to FIG. 2F, including a traversal level permutation function performed on the numbered chunks as listed child pointers in the parent manifest, in accordance with an embodiment of the present invention.



FIG. 3A presents a flow chart illustrating a method performed by a content producing device for encrypting manifest content based on permutation, in accordance with an embodiment of the present invention.



FIG. 3B presents a flow chart illustrating a method performed by a content producing device for encrypting manifest content based on permutation, in accordance with an embodiment of the present invention.



FIG. 4 presents a flow chart illustrating a method performed by a content requesting device for processing encrypted content of a manifest based on permutation, in accordance with an embodiment of the present invention.



FIG. 5 illustrates an exemplary computer and communication system that facilitates encryption of manifest content based on permutation, in accordance with an embodiment of the present invention





In the figures, like reference numerals refer to the same figure elements.


DETAILED DESCRIPTION

The following description is presented to enable any person skilled in the art to make and use the embodiments, and is provided in the context of a particular application and its requirements. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present disclosure. Thus, the present invention is not limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.


Overview

Embodiments of the present invention solve the problem of costly decryption procedures for each individual content object of a manifest by performing a permutation-based encryption on the content of the manifest. In CCN, a large piece of content, e.g., a movie, video, book, or a genome sequence, can be represented as a manifest, which is a content object that describes a collection of content objects and may include their corresponding digests. A manifest can include a name and a signature, thus providing trust to a requesting application for the content objects described by the manifest. Signing and verifying aggregates of content objects through the use of a secure content catalog (e.g., a manifest) is described in U.S. patent application Ser. No. 14/231,515 which is herein incorporated by reference. The content described by the manifest can be data objects or other manifests. A manifest contains an inherent order based on a tree-like topology of the collection of objects described by the manifest. In order to retrieve or reassemble the contents of a manifest, a system can traverse a manifest tree, which contains child and parent nodes ordered in the tree-like structure.


Thus, a manifest is a CCN content object that can be used to encode a larger “original” content object by including pointers or links to other “member” or “children” content objects (e.g., leaves) that contain the data that make up the larger content object encoded by the manifest. Because a manifest is itself a content object, a manifest can include links or children pointers to data objects (e.g., leaf nodes) or other manifests (e.g., non-leaf nodes). For example, given a manifest with the name “/a/b” that includes a list of three pointers to content (or chunks) identified by the names “/a/b/chunk1,” “/a/b/chunk2,” and “/a/b/chunk3,” the original content object encoded by the manifest is the concatenation of each of the three chunks, which are themselves content objects (“chunked content objects”). Reassembly of the content represented by the manifest is based on an in-order traversal of the manifest tree (e.g., by concatenating bytes from the leaf nodes to form the whole original content object). If the original content object is encrypted, the manifest can specify the decryption metadata (i.e., the keys) to be used for all children content objects to which the manifest points. The consumer must locate or obtain these decryption keys before reassembling the content object, which can involve decrypting each child content object in the manifest. However, decrypting each child content object in the manifest may involve computationally costly procedures and may also induce significant delays.


Embodiments of the present invention solve this problem by providing a technique to encrypt or hide the details of a content object by randomizing the reassembly strategy for a manifest. Some variations of the technique involve permuting the bytes of a leaf node (e.g., whole-content permutation, whole-chunk permutation, and chunk-level permutation), while other variations involve permuting the order of children nodes (or member content objects) visited during reassembly (e.g., traversal permutation). In addition, these variations may be combined to provide a hybrid permutation technique.


Specifically, given a collection of data or a large piece of content, a content producer can partition the collection of data into a set of content objects or chunks (or “chunked content objects”), and perform a permutation function on the set of chunked content objects. In “whole-content” permutation, a producer permutes all of the concatenated bytes of the chunked content objects. In “whole-chunk” permutation, the producer permutes the individual bytes that comprise each chunked content object. In “chunk-level” permutation, the producer permutes the entire set of chunked content objects, while leaving the bytes within each chunked content object intact. In “traversal” permutation, the producer permutes the ordered child pointers of a manifest. These various permutation techniques are described below in relation to FIGS. 2A-2G.


The producer can create a manifest based on the permuted content objects or chunks, and subsequently encode the permutation function and the permuted content objects in the manifest. In other words, the producer can build a manifest tree based on the permuted content objects, and further encode the permutation function in the manifest, as described further below.


A content consumer that receives the manifest can obtain or extract the permutation function, as described below in relation to FIG. 4, and use the permutation function to reassemble the original collection of data, without performing any additional computation. Thus, embodiments of the present invention allow a producer to permute content indicated by a manifest, and indicate the permutation function in the manifest. This allows a consumer that receives the manifest to perform a secure reassembly, which results in reduced time and a more efficient distribution of digital data.


Thus, these results provide improvements to the distribution of digital content, where the improvements are fundamentally technological. Embodiments of the present invention provide a technological solution (e.g., transmitting large amounts of digital data via permutation-based content encryption of a manifest) to the technological problem of the efficient, secure, and effective distribution of digital content.


In examples described in this disclosure, each piece of content is individually named, and each piece of data is bound to a unique name that distinguishes the data from any other piece of data, such as other versions of the same data or data from other sources. This unique name allows a network device to request the data by disseminating a request or an Interest that indicates the unique name, and can obtain the data independent from the data's storage location, network location, application, and means of transportation. The following terms are used to describe the CCN architecture:


Content Object (or “Content Object”):


A single piece of named data, which is bound to a unique name. Content Objects are “persistent,” which means that a Content Object can move around within a computing device, or across different computing devices, but does not change. If any component of the Content Object changes, the entity that made the change creates a new Content Object that includes the updated content, and binds the new Content Object to a new unique name.


Unique Names:


A name in a CCN is typically location independent and uniquely identifies a Content Object. A data-forwarding device can use the name or name prefix to forward a packet toward a network node that generates or stores the Content Object, regardless of a network address or physical location for the Content Object. In some embodiments, the name may be a hierarchically structured variable-length identifier (HSVLI). The HSVLI can be divided into several hierarchical components, which can be structured in various ways. For example, the individual name components parc, home, ccn, and test.txt can be structured in a left-oriented prefix-major fashion to form the name “/parc/home/ccn/test.txt.” Thus, the name “/parc/home/ccn” can be a “parent” or “prefix” of “/parc/home/ccn/test.txt.” Additional components can be used to distinguish between different versions of the content item, such as a collaborative document. In some embodiments, the name can include a non-hierarchical identifier, such as a hash value that is derived from the Content Object's data (e.g., a checksum value) and/or from elements of the Content Object's name. A description of a hash-based name is described in U.S. patent application Ser. No. 13/847,814. A name can also be a flat label. Hereinafter, “name” is used to refer to any name for a piece of data in a name-data network, such as a hierarchical name or name prefix, a flat name, a fixed-length name, an arbitrary-length name, or a label (e.g., a Multiprotocol Label Switching (MPLS) label).


Interest (or “Interest”):


A packet that indicates a request for a piece of data, and includes a name (or a name prefix) for the piece of data. A data consumer can disseminate a request or Interest across an information-centric network, which CCN routers can propagate toward a storage device (e.g., a cache server) or a data producer that can provide the requested data to satisfy the request or Interest.


The methods disclosed herein are not limited to CCN networks and are applicable to other architectures as well. A description of a CCN architecture is described in U.S. patent application Ser. No. 12/338,175 which is herein incorporated by reference.


Network Architecture and Overview of Order Encoded Manifest



FIG. 1 illustrates an exemplary computing environment that facilitates encryption of manifest content based on permutation, in accordance with an embodiment of the present invention. Network 100 can include a content requesting device 116, a content producing device 118, and a router or other forwarding device at nodes 102, 104, 106, 108, 110, 112, and 114. A node can be a computer system, an end-point representing users, and/or a device that can generate interests or originate content. A node can also be an edge router (e.g., CCN nodes 102, 104, 112, and 114) or a core router (e.g., intermediate CCN routers 106, 108, and 110). During operation, client computing device 116 can generate and send an interest 130 with a name 130.1 of “/manifest_name,” which also indicates a collection of data. Interest 130 can travel through a network (such as a CCN) via nodes or routers 102, 110, and 112, finally reaching content producing device or producer 118. Producer 118 can generate and transmit a responsive content object, which can be a manifest 140 with a manifest name 142 (that has a value of, e.g., “/manifest_name”), a permutation function 144, a list of content objects by names 140.1-140.n and corresponding content object hashes or digests 142.1-142.n, and a producer signature 146. Manifest 140 can travel back to device 116 via a reverse path (e.g., routers 112, 110, and 102).


Device 116 can receive manifest 140 and obtain permutation function 144. Permutation function 144 may be embedded directly in manifest 140, indicated as a link, or indicated via a secure channel. Device 116 may perform a retrieval procedure that involves a cryptographic operation (such as requesting the permutation function information based on a public key, asymmetric key, digital certificate, or other method). Once in possession of the permutation function, device 116 can retrieve the permuted content objects of manifest 140, and reassemble the retrieved permuted content objects by using the obtained permutation function. In this way, device 116 can avoid having to perform additional computation, e.g., a costly computation procedure associated with each individually retrieved content object. Instead, device 116 need only reassemble or rearrange the retrieved content objects based on the permutation function. The only cryptographic operation performed by device 116 may be retrieving the permutation function, depending on how the permutation function is indicated in the manifest.


Exemplary Manifest Tree


FIG. 2A presents an exemplary manifest tree 200 illustrating partitioned collections of data, in accordance with an embodiment of the present invention. Manifest tree 200 can represent a large collection of data, which can be a single large content object, and can be represented by a manifest hierarchy 202. Specifically, a content producer can partition a data collection into n content objects 212-248, and can create a manifest hierarchy 202 for the partitioned collection. Manifest hierarchy 202 can include one or more levels of manifests, such that higher-level manifests (e.g., root manifest 204) reference a next-level manifest (e.g., manifests 206, 208, and 210) via its name or self-certifying name. Manifests with self-certifying names are described, respectively, in U.S. application Ser. No. 14/231,515. The content producer can create a set of p manifests for the n content objects 212-248. While manifest hierarchy 202 depicts a complete tree, in practice, manifest hierarchy can include any tree structure that maintains an in-order traversal order.


The individual manifests in manifest hierarchy 202 may each include an arbitrary number of links or pointers to children or member content objects. For example, manifest 206 can include links to content objects 212-220 (which comprise a partitioned collection of data 211), manifest 208 can include links to content objects 232-240 (which comprise a partitioned collection of data 231), and manifest 210 can include links to content objects 242-248 (which comprise a partitioned collection of data 241). Just as root manifest 204 is a content object that represents a large collection of data, so is manifest 206 a content object that represents a (partitioned) collection of data.


Whole-Content Permutation


Assume the following notations: let “CO” be a content object of size “|CO|” in bytes and size “∥CO∥” in chunks; let “COi” be the i-th chunk of a content object of size “|COi|” in bytes; let M be a manifest with “|M|” entries; let “Mi” be the i-th entry in a manifest; and let “p(i,j)” be the permutation of the integers from i to j (i<j), inclusive.



FIG. 2B presents an exemplary manifest 206 with child content object chunks, including a whole-content permutation function performed on the concatenated bytes of a partitioned collection of data, in accordance with an embodiment of the present invention. Content object 211 corresponds to partitioned collection of data 211 of FIG. 2A and includes a set of content objects or chunks 212, 214, 216, 218, and 220. In some embodiments, chunks 212-220 can each include the same number of bytes.


In whole-content permutation, a producer can perform a permutation function on all of the concatenated bytes of a large content object before encoding it with a manifest. The producer can generate a permutation p(1, |CO|), and shuffle the bytes of CO based on this permutation, forming the encrypted version, CO′. The producer can then create a manifest tree by chunking the encrypted bytes CO′. For example, the producer can generate a permutation p(i, |CO|), where |CO| is the total size in bytes of content object 211, which results in rearranging the bytes comprising the concatenation of chunks 212-220. The producer can subsequently build manifest 206 based on the permuted bytes of content object 211. Because the permutation applies to the entire content object 211, the permutation function p is stored in the root manifest (i.e., manifest 206) that represents the content object.


Whole-Chunk Permutation



FIG. 2C presents an exemplary manifest 206 with child content object chunks, including a whole-chunk permutation function performed on the bytes of each chunk of a partitioned collection of data, in accordance with an embodiment of the present invention. In whole-chunk permutation, a producer can perform a permutation function on the bytes of each content object chunk COi before encoding it with a manifest. The producer can generate a permutation p(1,|COi|), shuffle the bytes of each COi in the same way, and create a manifest tree based on the permuted chunks. For example, the producer can generate a permutation p(1,|COi|), where |COi| is the total size in bytes of each content object chunk (e.g., chunk 212), which results in rearranging the bytes comprising each individual content object chunk. The producer can then build manifest 206 based on the permuted chunks of content object 211. Because the permutation applies to the entire content object 211 by touching each chunk, the permutation function p is stored in the root manifest (i.e., manifest 206) that represents the content object.


Chunk-Level Permutation



FIG. 2D presents an exemplary manifest 206 with child content object chunks, which illustrates the numbered chunks of a partitioned collection of data before a chunk-level permutation function is performed on the numbered chunks, in accordance with an embodiment of the present invention. In chunk-level permutation, a producer can perform a permutation function on the individual chunks of the content object. The producer can generate a permutation p(1,∥CO∥), shuffle the content object chunks, and create a manifest tree based on the permuted chunks. This technique leaves the bytes within each chunk intact. For example, the producer can generate a permutation p(1,∥CO∥), where ∥CO∥ is the total size in chunks of content object 211, which results in rearranging the chunks comprising content object 211. The producer can then build manifest 206 based on the shuffled chunks of content object 211, as shown in FIG. 2E.



FIG. 2E presents an exemplary manifest with child content object chunks corresponding to FIG. 2D, including a chunk-level permutation function performed on the numbered chunks, in accordance with an embodiment of the present invention. For a set of content object chunks ordered {1, 2, 3, 4, 5}, the producer can perform a chunk-level permutation, as described above in relation to FIG. 2D, which shuffles the chunks of content object 211 to result in a set of content object chunks ordered {3, 1, 2, 5, 4}. Because the permutation applies to the entire content object 211 by shuffling every chunk, the permutation function p is stored in the root manifest (i.e., manifest 206) that represents the content object.


Traversal Permutation



FIG. 2F presents an exemplary manifest 206 with child content object chunks, which illustrates the numbered chunks of a partitioned collection of data before a traversal permutation function is performed on the numbered chunks, in accordance with an embodiment of the present invention. In traversal permutation, a producer can perform a permutation function on the ordered of pointers to child content object in a manifest. Given a manifest M, the producer can generate a permutation p(1,|M|) and shuffle or permute the order of the child pointers. Let manifest M be manifest 206, which includes a name 250 of “/manifest206_name,” a permutation function 252 with a value of “Traversal_Permutation,” and a list of pointers to content objects based on content object names 254.1-254.5 (e.g., “Name_Chunk_1,” “Name_Chunk_2,” etc.). The producer can generate a permutation p(i,|M|), where |M| is the number of entries in M and is equal to 5, which results in rearranging the ordered list of entries in M, as shown below in FIG. 2G.



FIG. 2G presents an exemplary manifest with child content object chunks corresponding to FIG. 2F, including a traversal level permutation function performed on the numbered chunks as listed child pointers in the parent manifest, in accordance with an embodiment of the present invention. Manifest 206 can include a name 250 of “/manifest206_name”, a permutation function 252 with a value of “Traversal_Permutation,” and a list of shuffled pointers to content objects based on content object names 254.1-254.5. That is, the child pointers in manifest 206 are shuffled from an order of {1, 2, 3, 4, 5} to an order of {3, 1, 2, 5, 4}, where the new shuffled order corresponds to “Name_Chunk_3,” “Name_Chunk_1,” “Name_Chunk_2,” “Name_Chunk_5,” and “Name_Chunk_4.” Because the permutation applies to only a subset of the content object represented by either a root manifest or a child (non-leaf) manifest (such as manifest 206), the permutation function p is stored in the manifest to which the permutation is applied (i.e., manifest 206).


Note that chunk-level permutation and traversal permutation are associated in that both chunk-level permutation (on the chunks of the larger content object) and traversal permutation (on the ordered child pointers of a manifest) result in a manifest with shuffled pointers to chunks.


Content Producer Encrypts Manifest Content Based on Permutation



FIG. 3A presents a flow chart 300 illustrating a method performed by a content producing device for encrypting manifest content based on permutation, in accordance with an embodiment of the present invention. During operation, the system partitions, by a content producing device, a collection of data into a first set of content objects, wherein a content object is a chunk comprised of a plurality of bits (operation 302). In some embodiments, each chunk is of a fixed size. The system performs a first permutation function on the first set of content object to obtain a first set of permuted content objects (operation 304). The first permutation function can be a whole-content permutation, a whole-chunk permutation, or a chunk-level permutation, or a hybrid of these permutations, as described above. For example, the system can perform the first permutation function on the bytes comprising an ordered concatenation of the content objects of the first set (whole-content permutation) (operation 306). The system can also or alternatively perform the first permutation function on the bytes comprising each content object of the first set (whole-chunk permutation) (operation 308). The system can also or alternatively perform the first permutation function on each chunk of the partitioned collection of data (chunk-level permutation) (operation 310). Note that the bytes comprising each individual chunk remain unchanged in the chunk-level permutation.


The system creates a manifest based on the permuted content objects (operation 312). Recall that a manifest is itself a content object which indicates a set of content objects which are data objects or other manifests. A manifest can also indicate the set of content objects in a particular order, e.g., as pointers based on a tree-like topology of the data represented by the manifest. In some embodiments, the system performs a second permutation function on the ordered child pointers of the manifest (traversal permutation) (operation 314). Traversal permutation can occur as a result of or in advance of chunk-level permutation. The system encodes in the manifest the first permutation function by embedding, including a link, or indicating a secure channel (operation 316). The system also encodes in the manifest the permuted content objects based on a tree-like topology (operation 318), as described above in relation to FIG. 2A.



FIG. 3B presents a flow chart 350 illustrating a method performed by a content producing device for encrypting manifest content based on permutation, in accordance with an embodiment of the present invention. During operation, the system receives, by a content producing device, a request for a manifest based on a name for the manifest (operation 352). In response to the request for the manifest, the system generates the manifest, which encodes a first permutation function and a set of permuted content objects (operation 354). The system transmits the manifest (operation 356). In some embodiments, in response to receiving and verifying a request for the first permutation function, the system transmits the first permutation function (operation 358). Specifically, the request and response can be for information which indicates the first permutation function. In response to receiving interests for content indicated in the manifest, the system can transmit the responsive content objects (operation 360). Note that the manifest can point to both content that can be satisfied by the content producing device as well as content that cannot be satisfied by the content producing device (i.e., content owned or published by another entity). There are no restrictions on the location of the content indicated in the manifest.


Content Consumer Processes Encrypted Manifest Based on Permutation



FIG. 4 presents a flow chart 400 illustrating a method performed by a content requesting device for processing encrypted content of a manifest based on permutation, in accordance with an embodiment of the present invention. During operation, the system transmits, by a content requesting device, a request for a manifest based on a name for the manifest (operation 402). In response to the request for the manifest, the system receives a manifest which encodes a first permutation function and a set of permuted content objects (operation 404). The system retrieves the first permutation function encoded in the manifest (operation 406). Recall that the first permutation function can be directly embedded, linked, or indicated as retrieveable over a secure channel. Thus, in some embodiments, in response to transmitting a request for the first permutation function, the system receives the first permutation function (operation 408).


In response to transmitting interests for the content indicated in the manifest, the system receives responsive content objects (operation 410). The system reassembles the received content object based on the first permutation function, without performing any additional computation (operation 412).


Exemplary Computer and Communication System


FIG. 5 illustrates an exemplary computer and communication system that facilitates encryption of manifest content based on permutation, in accordance with an embodiment of the present invention. Computer and communication system 502 includes a processor 504, a memory 506, and a storage device 508. Memory 506 can include a volatile memory (e.g., RAM) that serves as a managed memory, and can be used to store one or more memory pools. Furthermore, computer and communication system 502 can be coupled to a display device 510, a keyboard 512, and a pointing device 514. Storage device 508 can store an operating system 516, a content-processing system 518, and data 530.


Content-processing system 518 can include instructions, which when executed by computer and communication system 502, can cause computer and communication system 502 to perform methods and/or processes described in this disclosure. Specifically, content-processing system 518 may include instructions for partitioning, by a computer system, a collection of data into a first set of content objects, wherein a content object of the first set is a chunk comprised of a plurality of bytes (data-partitioning module 522). Content-processing system 518 can include instructions for performing a first permutation function on the first set of content objects to obtain a first set of permuted content objects (permutation-performing module 524). Content-processing system 518 can also include instructions for creating a manifest based on the permuted content objects, wherein a manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest (manifest-creating module 526). Content-processing system 518 can include instructions for encoding the first permutation function and the permuted content objects in the manifest (manifest-encoding module).


Content-processing system 518 can further include instructions for performing a second permutation function on an order of child pointers which correspond to content objects indicated in the manifest (permutation-performing module 524). Content-processing system 518 can include instructions for encoding the second permutation function in the manifest (manifest-encoding module 528).


Data 530 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure. Specifically, data 530 can store at least: a collection of data; a content object; a partitioned collection of data that is a content object; a name; a manifest; a manifest or root manifest that indicates a set of content objects and/or their corresponding digests; a data object; a name associated with each content object; a name that is a hierarchically structured variable length identifier which comprises contiguous name components ordered from a most general level to a most specific level; a permutation function; a set of permuted content objects or chunks; a manifest that encodes a permutation function and a set of permuted content objects or chunks; ordered and permuted bytes comprising an ordered concatenation of chunked content objects; ordered and permuted bytes comprising an chunked content object; ordered and permuted chunks of a content object; ordered and permuted list of pointers to content objects; Lehmer codes; a symmetric block cipher; an encryption algorithm; a form of permutation encoding; and information indicating a permutation function.


The data structures and code described in this detailed description are typically stored on a computer-readable storage medium, which may be any device or medium that can store code and/or data for use by a computer system. The computer-readable storage medium includes, but is not limited to, volatile memory, non-volatile memory, magnetic and optical storage devices such as disk drives, magnetic tape, CDs (compact discs), DVDs (digital versatile discs or digital video discs), or other media capable of storing computer-readable media now known or later developed.


The methods and processes described in the detailed description section can be embodied as code and/or data, which can be stored in a computer-readable storage medium as described above. When a computer system reads and executes the code and/or data stored on the computer-readable storage medium, the computer system performs the methods and processes embodied as data structures and code and stored within the computer-readable storage medium.


Furthermore, the methods and processes described above can be included in hardware modules or apparatus. The hardware modules or apparatus can include, but are not limited to, application-specific integrated circuit (ASIC) chips, field-programmable gate arrays (FPGAs), dedicated or shared processors that execute a particular software module or a piece of code at a particular time, and other programmable-logic devices now known or later developed. When the hardware modules or apparatus are activated, they perform the methods and processes included within them.


The foregoing descriptions of embodiments of the present invention have been presented for purposes of illustration and description only. They are not intended to be exhaustive or to limit the present invention to the forms disclosed. Accordingly, many modifications and variations will be apparent to practitioners skilled in the art. Additionally, the above disclosure is not intended to limit the present invention. The scope of the present invention is defined by the appended claims.

Claims
  • 1. A computer-implemented method for encoding content, comprising: receiving, by a computer system, a request for a manifest from an authorized entity;partitioning, by the computer system, a collection of data into a first set of content objects, wherein a content object of the first set of content objects is a chunk comprised of a plurality of bytes;performing, by the computer system, a first permutation function on the first set of content objects to obtain a first set of permuted content objects;creating, by the computer system, the manifest based on the permuted content objects, wherein the manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest;performing, by the computer system, a second permutation function on an order of child pointers which correspond to content objects indicated in the manifest;encoding, by the computer system, the first permutation function, the second permutation function, and the permuted content objects in the manifest, thereby facilitating the authorized entity that receives the manifest to reassemble the manifest contents based on a permutation function, wherein encoding the first permutation function in the manifest includes indicating a secure channel over which to retrieve the first permutation function; andproviding, by the computer system, the manifest to the authorized entity.
  • 2. The method of claim 1, wherein the first permutation function is performed on one or more of: bytes comprising an ordered concatenation of the chunks of the first set of content objects;bytes comprising each chunk of the first set of content objects; andeach chunk of the partitioned collection of data, wherein the bytes comprising a respective chunk are not permuted.
  • 3. The method of claim 1, wherein the manifest indicates the second set of content objects based on a direct embedding of a respective content object or a child pointer to a respective content object.
  • 4. The method of claim 1, wherein encoding the first permutation function in the manifest is based on an order of child pointers which correspond to each permuted content object of the first set of permuted content objects, and wherein encoding the permuted content objects in the manifest is based on a tree-like topology.
  • 5. The method of claim 1, wherein the first permutation function is based on one or more of: shuffling the bytes comprising the first set of content objects;Lehmer codes;a symmetric block cipher;an encryption algorithm; anda form of permutation encoding.
  • 6. The method of claim 1, wherein encoding the first permutation function in the manifest is based on one or more of: embedding in the manifest the first permutation function by including the first permutation function in decryption metadata associated with the manifest; andincluding in the manifest a link to retrieve the first permutation function, wherein a successful retrieval of the first permutation function via the link involves a verification of authentication information.
  • 7. The method of claim 1, further comprising: receiving, by the computer system, a request for the first permutation function from the authorized entity; andin response to the request for the first permutation function, providing the first permutation function to the authorized entity.
  • 8. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising: receiving, by a computer system, a request for a manifest from an authorized entity;partitioning, by the computer system, a collection of data into a first set of content objects, wherein a content object of the first set of content objects is a chunk comprised of a plurality of bytes;performing, by the computer system, a first permutation function on the first set of content objects to obtain a first set of permuted content objects;creating, by the computer system, the manifest based on the permuted content objects, wherein the manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest;performing, by the computer system, a second permutation function on an order of child pointers which correspond to content objects indicated in the manifest;encoding, by the computer system, the first permutation function, the second permutation function, and the permuted content objects in the manifest, thereby facilitating the authorized entity that receives the manifest to reassemble the manifest contents based on a permutation function, wherein encoding the first permutation function in the manifest includes indicating a secure channel over which to retrieve the first permutation function; andproviding, by the computer system, the manifest to the authorized entity.
  • 9. The storage medium of claim 8, wherein the first permutation function is performed on one or more of: bytes comprising an ordered concatenation of the chunks of the first set of content objects;bytes comprising each chunk of the first set of content objects; andeach chunk of the partitioned collection of data, wherein the bytes comprising a respective chunk are not permuted.
  • 10. The storage medium of claim 8, wherein the manifest indicates the second set of content objects based on a direct embedding of a respective content object or a child pointer to a respective content object.
  • 11. The storage medium of claim 8, wherein encoding the first permutation function in the manifest is based on an order of child pointers which correspond to each permuted content object of the first set of permuted content objects, and wherein encoding the permuted content objects in the manifest is based on a tree-like topology.
  • 12. The storage medium of claim 8, wherein encoding the first permutation function in the manifest is based on one or more of: embedding in the manifest the first permutation function by including the first permutation function in decryption metadata associated with the manifest; andincluding in the manifest a link to retrieve the first permutation function, wherein a successful retrieval of the first permutation function via the link involves a verification of authentication information.
  • 13. The storage medium of claim 8, wherein the first permutation function is based on one or more of: shuffling the bytes comprising the first set of content objects;Lehmer codes;a symmetric block cipher;an encryption algorithm; anda form of permutation encoding.
  • 14. A computer system for encoding content, the system comprising: a processor;a storage device coupled to the processor and storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:receiving, by a computer system, a request for a manifest from an authorized entity;partitioning, by the computer system, a collection of data into a first set of content objects, wherein a content object of the first set of content objects is a chunk comprised of a plurality of bytes;performing, by a computer system, a first permutation function on the first set of content objects to obtain a first set of permuted content objects;creating, by a computer system, the manifest based on the permuted content objects, wherein the manifest is a content object which indicates a second set of content objects, wherein a respective content object of the second set is a data object or another manifest;performing, by a computer system, a second permutation function on an order of child pointers which correspond to content objects indicated in the manifest;encoding, by a computer system, the first permutation function, the second permutation function, and the permuted content objects in the manifest, thereby facilitating the authorized entity that receives the manifest to reassemble the manifest contents based on a permutation function, wherein encoding the first permutation function in the manifest includes indicating a secure channel over which to retrieve the first permutation function; andproviding, by the computer system, the manifest to the authorized entity.
  • 15. The computer system of claim 14, wherein the first permutation function is performed on one or more of: bytes comprising an ordered concatenation of the chunks of the first set of content objects;bytes comprising each chunk of the first set of content objects; andeach chunk of the partitioned collection of data, wherein the bytes comprising a respective chunk are not permuted.
  • 16. The computer system of claim 14, wherein the manifest indicates the second set of content objects based on a direct embedding of a respective content object or a child pointer to a respective content object.
  • 17. The computer system of claim 14, wherein encoding the first permutation function in the manifest is based on an order of child pointers which correspond to each permuted content object of the first set of permuted content objects, and wherein encoding the permuted content objects in the manifest is based on a tree-like topology.
  • 18. The computer system of claim 14, wherein the first permutation function is based on one or more of: shuffling the bytes comprising the first set of content objects;Lehmer codes;a symmetric block cipher;an encryption algorithm; anda form of permutation encoding.
  • 19. The computer system of claim 14, wherein encoding the first permutation function in the manifest is based on one or more of: embedding in the manifest the first permutation function by including the first permutation function in decryption metadata associated with the manifest; andincluding in the manifest a link to retrieve the first permutation function, wherein a successful retrieval of the first permutation function via the link involves a verification of authentication information.
  • 20. The storage medium of claim 8, the method further comprising: receiving, by the computer system, a request for the first permutation function from the authorized entity; andin response to the request for the first permutation function, providing the first permutation function to the authorized entity.
US Referenced Citations (562)
Number Name Date Kind
817441 Niesz Apr 1906 A
4309569 Merkle Jan 1982 A
4921898 Lenney May 1990 A
5070134 Oyamada Dec 1991 A
5110856 Oyamada May 1992 A
5214702 Fischer May 1993 A
5377354 Scannell Dec 1994 A
5506844 Rao Apr 1996 A
5629370 Freidzon May 1997 A
5845207 Amin Dec 1998 A
5870605 Bracho Feb 1999 A
6052683 Irwin Apr 2000 A
6085320 Kaliski, Jr. Jul 2000 A
6091724 Chandra Jul 2000 A
6128623 Mattis Oct 2000 A
6128627 Mattis Oct 2000 A
6173364 Zenchelsky Jan 2001 B1
6209003 Mattis Mar 2001 B1
6226618 Downs May 2001 B1
6233617 Rothwein May 2001 B1
6233646 Hahm May 2001 B1
6289358 Mattis Sep 2001 B1
6292880 Mattis Sep 2001 B1
6332158 Risley Dec 2001 B1
6366988 Skiba Apr 2002 B1
6574377 Cahill Jun 2003 B1
6654792 Verma Nov 2003 B1
6667957 Corson Dec 2003 B1
6681220 Kaplan Jan 2004 B1
6681326 Son Jan 2004 B2
6732273 Byers May 2004 B1
6769066 Botros Jul 2004 B1
6772333 Brendel Aug 2004 B1
6775258 vanValkenburg Aug 2004 B1
6862280 Bertagna Mar 2005 B1
6901452 Bertagna May 2005 B1
6915307 Mattis Jul 2005 B1
6917985 Madruga Jul 2005 B2
6957228 Graser Oct 2005 B1
6968393 Chen Nov 2005 B1
6981029 Menditto Dec 2005 B1
7007024 Zelenka Feb 2006 B2
7013389 Srivastava Mar 2006 B1
7031308 Garcia-Luna-Aceves Apr 2006 B2
7043637 Bolosky May 2006 B2
7061877 Gummalla Jun 2006 B1
7080073 Jiang Jul 2006 B1
RE39360 Aziz Oct 2006 E
7149750 Chadwick Dec 2006 B2
7152094 Jannu Dec 2006 B1
7177646 ONeill Feb 2007 B2
7206860 Murakami Apr 2007 B2
7206861 Callon Apr 2007 B1
7210326 Kawamoto May 2007 B2
7246159 Aggarwal Jul 2007 B2
7257837 Xu Aug 2007 B2
7287275 Moskowitz Oct 2007 B2
7315541 Housel Jan 2008 B1
7339929 Zelig Mar 2008 B2
7350229 Lander Mar 2008 B1
7362727 ONeill Apr 2008 B1
7382787 Barnes Jun 2008 B1
7395507 Robarts Jul 2008 B2
7430755 Hughes Sep 2008 B1
7444251 Nikovski Oct 2008 B2
7466703 Arunachalam Dec 2008 B1
7472422 Agbabian Dec 2008 B1
7496668 Hawkinson Feb 2009 B2
7509425 Rosenberg Mar 2009 B1
7523016 Surdulescu Apr 2009 B1
7542471 Samuels Jun 2009 B2
7543064 Juncker Jun 2009 B2
7552233 Raju Jun 2009 B2
7555482 Korkus Jun 2009 B2
7555563 Ott Jun 2009 B2
7564812 Elliott Jul 2009 B1
7567547 Mosko Jul 2009 B2
7567946 Andreoli Jul 2009 B2
7580971 Gollapudi Aug 2009 B1
7623535 Guichard Nov 2009 B2
7636767 Lev-Ran Dec 2009 B2
7647507 Feng Jan 2010 B1
7660324 Oguchi Feb 2010 B2
7685290 Satapati Mar 2010 B2
7698463 Ogier Apr 2010 B2
7698559 Chaudhury Apr 2010 B1
7769887 Bhattacharyya Aug 2010 B1
7779467 Choi Aug 2010 B2
7801069 Cheung Sep 2010 B2
7801177 Luss Sep 2010 B2
7816441 Elizalde Oct 2010 B2
7831733 Sultan Nov 2010 B2
7873619 Faibish Jan 2011 B1
7908337 Garcia-Luna-Aceves Mar 2011 B2
7924837 Shabtay Apr 2011 B1
7953014 Toda May 2011 B2
7953885 Devireddy May 2011 B1
7979912 Roka Jul 2011 B1
8000267 Solis Aug 2011 B2
8010691 Kollmansberger Aug 2011 B2
8069023 Frailong Nov 2011 B1
8074289 Carpentier Dec 2011 B1
8117441 Kurien Feb 2012 B2
8160069 Jacobson Apr 2012 B2
8204060 Jacobson Jun 2012 B2
8214364 Bigus Jul 2012 B2
8224985 Takeda Jul 2012 B2
8225057 Zheng Jul 2012 B1
8271578 Sheffi Sep 2012 B2
8271687 Turner Sep 2012 B2
8312064 Gauvin Nov 2012 B1
8332357 Chung Dec 2012 B1
8386622 Jacobson Feb 2013 B2
8447851 Anderson May 2013 B1
8462781 McGhee Jun 2013 B2
8467297 Liu Jun 2013 B2
8473633 Eardley Jun 2013 B2
8553562 Allan Oct 2013 B2
8572214 Garcia-Luna-Aceves Oct 2013 B2
8654649 Vasseur Feb 2014 B2
8665757 Kling Mar 2014 B2
8667172 Ravindran Mar 2014 B2
8677451 Bhimaraju Mar 2014 B1
8688619 Ezick Apr 2014 B1
8699350 Kumar Apr 2014 B1
8718055 Vasseur May 2014 B2
8750820 Allan Jun 2014 B2
8761022 Chiabaut Jun 2014 B2
8762477 Xie Jun 2014 B2
8762570 Qian Jun 2014 B2
8762707 Killian Jun 2014 B2
8767627 Ezure Jul 2014 B2
8817594 Gero Aug 2014 B2
8826381 Kim Sep 2014 B2
8832302 Bradford Sep 2014 B1
8836536 Marwah Sep 2014 B2
8861356 Kozat Oct 2014 B2
8862774 Vasseur Oct 2014 B2
8868779 ONeill Oct 2014 B2
8874842 Kimmel Oct 2014 B1
8880682 Bishop Nov 2014 B2
8903756 Zhao Dec 2014 B2
8923293 Jacobson Dec 2014 B2
8934496 Vasseur Jan 2015 B2
8937865 Kumar Jan 2015 B1
8972969 Gaither Mar 2015 B2
8977596 Montulli Mar 2015 B2
9002921 Westphal Apr 2015 B2
9032095 Traina May 2015 B1
9071498 Beser Jun 2015 B2
9112895 Lin Aug 2015 B1
9253087 Zhang Feb 2016 B2
9280610 Gruber Mar 2016 B2
9513762 Hakim Dec 2016 B1
20020002680 Carbajal Jan 2002 A1
20020010795 Brown Jan 2002 A1
20020038296 Margolus Mar 2002 A1
20020048269 Hong Apr 2002 A1
20020054593 Morohashi May 2002 A1
20020077988 Sasaki Jun 2002 A1
20020078066 Robinson Jun 2002 A1
20020138551 Erickson Sep 2002 A1
20020152305 Jackson Oct 2002 A1
20020176404 Girard Nov 2002 A1
20020188605 Adya Dec 2002 A1
20020199014 Yang Dec 2002 A1
20030004621 Bousquet Jan 2003 A1
20030009365 Tynan Jan 2003 A1
20030033394 Stine Feb 2003 A1
20030046396 Richter Mar 2003 A1
20030046421 Horvitz et al. Mar 2003 A1
20030046437 Eytchison Mar 2003 A1
20030048793 Pochon Mar 2003 A1
20030051100 Patel Mar 2003 A1
20030061384 Nakatani Mar 2003 A1
20030074472 Lucco Apr 2003 A1
20030088696 McCanne May 2003 A1
20030097447 Johnston May 2003 A1
20030099237 Mitra May 2003 A1
20030140257 Peterka Jul 2003 A1
20030229892 Sardera Dec 2003 A1
20040024879 Dingman Feb 2004 A1
20040030602 Rosenquist Feb 2004 A1
20040064737 Milliken Apr 2004 A1
20040071140 Jason Apr 2004 A1
20040073617 Milliken Apr 2004 A1
20040073715 Folkes Apr 2004 A1
20040139230 Kim Jul 2004 A1
20040196783 Shinomiya Oct 2004 A1
20040221047 Grover Nov 2004 A1
20040225627 Botros Nov 2004 A1
20040233916 Takeuchi Nov 2004 A1
20040246902 Weinstein Dec 2004 A1
20040252683 Kennedy Dec 2004 A1
20050003832 Osafune Jan 2005 A1
20050028156 Hammond Feb 2005 A1
20050043060 Brandenberg Feb 2005 A1
20050050211 Kaul Mar 2005 A1
20050074001 Mattes Apr 2005 A1
20050132207 Mourad Jun 2005 A1
20050149508 Deshpande Jul 2005 A1
20050159823 Hayes Jul 2005 A1
20050198351 Nog Sep 2005 A1
20050249196 Ansari Nov 2005 A1
20050259637 Chu Nov 2005 A1
20050262217 Nonaka Nov 2005 A1
20050281288 Banerjee Dec 2005 A1
20050286535 Shrum Dec 2005 A1
20050289222 Sahim Dec 2005 A1
20060010249 Sabesan Jan 2006 A1
20060029102 Abe Feb 2006 A1
20060039379 Abe Feb 2006 A1
20060051055 Ohkawa Mar 2006 A1
20060072523 Richardson Apr 2006 A1
20060099973 Nair May 2006 A1
20060129514 Watanabe Jun 2006 A1
20060133343 Huang Jun 2006 A1
20060146686 Kim Jul 2006 A1
20060173831 Basso Aug 2006 A1
20060193295 White Aug 2006 A1
20060203804 Whitmore Sep 2006 A1
20060206445 Andreoli Sep 2006 A1
20060215684 Capone Sep 2006 A1
20060223504 Ishak Oct 2006 A1
20060242155 Moore Oct 2006 A1
20060256767 Suzuki Nov 2006 A1
20060268792 Belcea Nov 2006 A1
20070019619 Foster Jan 2007 A1
20070073888 Madhok Mar 2007 A1
20070094265 Korkus Apr 2007 A1
20070112880 Yang May 2007 A1
20070124412 Narayanaswami May 2007 A1
20070127457 Mirtorabi Jun 2007 A1
20070160062 Morishita Jul 2007 A1
20070162394 Zager Jul 2007 A1
20070171828 Dalal Jul 2007 A1
20070189284 Kecskemeti Aug 2007 A1
20070195765 Heissenbuttel Aug 2007 A1
20070204011 Shaver Aug 2007 A1
20070209067 Fogel Sep 2007 A1
20070239892 Ott Oct 2007 A1
20070240207 Belakhdar Oct 2007 A1
20070245034 Retana Oct 2007 A1
20070253418 Shiri Nov 2007 A1
20070255677 Alexander Nov 2007 A1
20070255699 Sreenivas Nov 2007 A1
20070255781 Li Nov 2007 A1
20070274504 Maes Nov 2007 A1
20070275701 Jonker Nov 2007 A1
20070276907 Maes Nov 2007 A1
20070283158 Danseglio Dec 2007 A1
20070294187 Scherrer Dec 2007 A1
20080005056 Stelzig Jan 2008 A1
20080005223 Flake Jan 2008 A1
20080010366 Duggan Jan 2008 A1
20080037420 Tang Feb 2008 A1
20080043989 Furutono Feb 2008 A1
20080046340 Brown Feb 2008 A1
20080059631 Bergstrom Mar 2008 A1
20080080440 Yarvis Apr 2008 A1
20080082662 Dandliker Apr 2008 A1
20080101357 Iovanna May 2008 A1
20080107034 Jetcheva May 2008 A1
20080107259 Satou May 2008 A1
20080123862 Rowley May 2008 A1
20080133583 Artan Jun 2008 A1
20080133755 Pollack Jun 2008 A1
20080151755 Nishioka Jun 2008 A1
20080159271 Kutt Jul 2008 A1
20080165775 Das Jul 2008 A1
20080186901 Itagaki Aug 2008 A1
20080200153 Fitzpatrick Aug 2008 A1
20080215669 Gaddy Sep 2008 A1
20080216086 Tanaka Sep 2008 A1
20080243992 Jardetzky Oct 2008 A1
20080250006 Dettinger Oct 2008 A1
20080256138 Sim-Tang Oct 2008 A1
20080256359 Kahn Oct 2008 A1
20080270618 Rosenberg Oct 2008 A1
20080271143 Stephens Oct 2008 A1
20080287142 Keighran Nov 2008 A1
20080288580 Wang Nov 2008 A1
20080298376 Takeda Dec 2008 A1
20080320148 Capuozzo Dec 2008 A1
20090006659 Collins Jan 2009 A1
20090013324 Gobara Jan 2009 A1
20090022154 Kiribe Jan 2009 A1
20090024641 Quigley Jan 2009 A1
20090030978 Johnson Jan 2009 A1
20090037763 Adhya Feb 2009 A1
20090052660 Chen Feb 2009 A1
20090067429 Nagai Mar 2009 A1
20090077184 Brewer Mar 2009 A1
20090092043 Lapuh Apr 2009 A1
20090097631 Gisby Apr 2009 A1
20090103515 Pointer Apr 2009 A1
20090113068 Fujihira Apr 2009 A1
20090116393 Hughes May 2009 A1
20090117922 Bell May 2009 A1
20090132662 Sheridan May 2009 A1
20090135728 Shen May 2009 A1
20090144300 Chatley Jun 2009 A1
20090157887 Froment Jun 2009 A1
20090185745 Momosaki Jul 2009 A1
20090193101 Munetsugu Jul 2009 A1
20090198832 Shah Aug 2009 A1
20090222344 Greene Sep 2009 A1
20090228593 Takeda Sep 2009 A1
20090254572 Redlich Oct 2009 A1
20090268905 Matsushima Oct 2009 A1
20090274158 Sharp Nov 2009 A1
20090276396 Gorman Nov 2009 A1
20090285209 Stewart Nov 2009 A1
20090287835 Jacobson Nov 2009 A1
20090287853 Carson Nov 2009 A1
20090288076 Johnson Nov 2009 A1
20090288143 Stebila Nov 2009 A1
20090288163 Jacobson Nov 2009 A1
20090292743 Bigus Nov 2009 A1
20090293121 Bigus Nov 2009 A1
20090300079 Shitomi Dec 2009 A1
20090300407 Kamath Dec 2009 A1
20090300512 Ahn Dec 2009 A1
20090307333 Welingkar Dec 2009 A1
20090323632 Nix Dec 2009 A1
20100005061 Basco Jan 2010 A1
20100027539 Beverly Feb 2010 A1
20100046546 Ram Feb 2010 A1
20100057929 Merat Mar 2010 A1
20100058346 Narang Mar 2010 A1
20100088370 Wu Apr 2010 A1
20100094767 Miltonberger Apr 2010 A1
20100094876 Huang Apr 2010 A1
20100098093 Ejzak Apr 2010 A1
20100100465 Cooke Apr 2010 A1
20100103870 Garcia-Luna-Aceves Apr 2010 A1
20100124191 Vos May 2010 A1
20100125911 Bhaskaran May 2010 A1
20100131660 Dec May 2010 A1
20100150155 Napierala Jun 2010 A1
20100165976 Khan Jul 2010 A1
20100169478 Saha Jul 2010 A1
20100169503 Kollmansberger Jul 2010 A1
20100180332 Ben-Yochanan Jul 2010 A1
20100182995 Hwang Jul 2010 A1
20100185753 Liu Jul 2010 A1
20100195653 Jacobson Aug 2010 A1
20100195654 Jacobson Aug 2010 A1
20100195655 Jacobson Aug 2010 A1
20100217874 Anantharaman Aug 2010 A1
20100217985 Fahrny Aug 2010 A1
20100232402 Przybysz Sep 2010 A1
20100232439 Dham Sep 2010 A1
20100235516 Nakamura Sep 2010 A1
20100246549 Zhang Sep 2010 A1
20100250497 Redlich Sep 2010 A1
20100250939 Adams Sep 2010 A1
20100257149 Cognigni Oct 2010 A1
20100268782 Zombek Oct 2010 A1
20100272107 Papp Oct 2010 A1
20100281263 Ugawa Nov 2010 A1
20100284309 Allan Nov 2010 A1
20100284404 Gopinath Nov 2010 A1
20100293293 Beser Nov 2010 A1
20100322249 Thathapudi Dec 2010 A1
20110013637 Xue Jan 2011 A1
20110019674 Iovanna Jan 2011 A1
20110022812 vanderLinden Jan 2011 A1
20110029952 Harrington Feb 2011 A1
20110055392 Shen Mar 2011 A1
20110055921 Narayanaswamy Mar 2011 A1
20110060716 Forman Mar 2011 A1
20110060717 Forman Mar 2011 A1
20110090908 Jacobson Apr 2011 A1
20110106755 Hao May 2011 A1
20110137919 Ryu Jun 2011 A1
20110145597 Yamaguchi Jun 2011 A1
20110145858 Philpott Jun 2011 A1
20110149858 Hwang Jun 2011 A1
20110153840 Narayana Jun 2011 A1
20110158122 Murphy Jun 2011 A1
20110161408 Kim Jun 2011 A1
20110202609 Chaturvedi Aug 2011 A1
20110219093 Ragunathan Sep 2011 A1
20110219427 Hito Sep 2011 A1
20110219727 May Sep 2011 A1
20110225293 Rathod Sep 2011 A1
20110231578 Nagappan Sep 2011 A1
20110239256 Gholmieh Sep 2011 A1
20110258049 Ramer Oct 2011 A1
20110264824 Venkata Subramanian Oct 2011 A1
20110265159 Ronda Oct 2011 A1
20110265174 Thornton Oct 2011 A1
20110271007 Wang Nov 2011 A1
20110286457 Ee Nov 2011 A1
20110286459 Rembarz Nov 2011 A1
20110295783 Zhao Dec 2011 A1
20110299454 Krishnaswamy Dec 2011 A1
20120011170 Elad Jan 2012 A1
20120011551 Levy Jan 2012 A1
20120023113 Ferren Jan 2012 A1
20120036180 Thornton Feb 2012 A1
20120047361 Erdmann Feb 2012 A1
20120066727 Nozoe Mar 2012 A1
20120106339 Mishra May 2012 A1
20120114313 Phillips May 2012 A1
20120120803 Farkas May 2012 A1
20120127994 Ko May 2012 A1
20120136676 Goodall May 2012 A1
20120136936 Quintuna May 2012 A1
20120136945 Lee May 2012 A1
20120137367 Dupont May 2012 A1
20120141093 Yamaguchi Jun 2012 A1
20120155464 Kim Jun 2012 A1
20120158973 Jacobson Jun 2012 A1
20120163373 Lo Jun 2012 A1
20120166433 Tseng Jun 2012 A1
20120170913 Isozaki Jul 2012 A1
20120179653 Araki Jul 2012 A1
20120197690 Agulnek Aug 2012 A1
20120198048 Ioffe Aug 2012 A1
20120221150 Arensmeier Aug 2012 A1
20120224487 Hui Sep 2012 A1
20120226902 Kim Sep 2012 A1
20120257500 Lynch Oct 2012 A1
20120284791 Miller Nov 2012 A1
20120290669 Parks Nov 2012 A1
20120290919 Melnyk Nov 2012 A1
20120291102 Cohen Nov 2012 A1
20120307629 Vasseur Dec 2012 A1
20120314580 Hong Dec 2012 A1
20120317307 Ravindran Dec 2012 A1
20120322422 Frecks Dec 2012 A1
20120323933 He Dec 2012 A1
20120331112 Chatani Dec 2012 A1
20130024560 Vasseur Jan 2013 A1
20130041982 Shi Feb 2013 A1
20130051392 Filsfils Feb 2013 A1
20130054971 Yamaguchi Feb 2013 A1
20130060962 Wang Mar 2013 A1
20130061084 Barton Mar 2013 A1
20130066823 Sweeney Mar 2013 A1
20130073552 Rangwala Mar 2013 A1
20130074155 Huh Mar 2013 A1
20130090942 Robinson Apr 2013 A1
20130091539 Khurana Apr 2013 A1
20130110987 Kim May 2013 A1
20130111063 Lee May 2013 A1
20130132719 Kobayashi May 2013 A1
20130139245 Thomas May 2013 A1
20130151584 Westphal Jun 2013 A1
20130151646 Chidambaram Jun 2013 A1
20130152070 Bhullar Jun 2013 A1
20130163426 Beliveau Jun 2013 A1
20130166668 Byun Jun 2013 A1
20130173822 Hong Jul 2013 A1
20130182568 Lee Jul 2013 A1
20130182931 Fan Jul 2013 A1
20130185406 Choi Jul 2013 A1
20130191412 Kitamura Jul 2013 A1
20130197698 Shah Aug 2013 A1
20130198119 Eberhardt, III Aug 2013 A1
20130212185 Pasquero Aug 2013 A1
20130219038 Lee Aug 2013 A1
20130219081 Qian Aug 2013 A1
20130219478 Mahamuni Aug 2013 A1
20130223237 Hui Aug 2013 A1
20130227048 Xie Aug 2013 A1
20130227114 Vasseur Aug 2013 A1
20130227166 Ravindran Aug 2013 A1
20130242996 Varvello Sep 2013 A1
20130250809 Hui Sep 2013 A1
20130262365 Dolbear Oct 2013 A1
20130282854 Jang Oct 2013 A1
20130282860 Zhang Oct 2013 A1
20130282920 Zhang Oct 2013 A1
20130304758 Gruber Nov 2013 A1
20130304937 Lee Nov 2013 A1
20130325888 Oneppo Dec 2013 A1
20130329696 Xu Dec 2013 A1
20130332971 Fisher Dec 2013 A1
20130336103 Vasseur Dec 2013 A1
20130336323 Srinivasan Dec 2013 A1
20130339481 Hong Dec 2013 A1
20130343408 Cook Dec 2013 A1
20140003232 Guichard Jan 2014 A1
20140003424 Matsuhira Jan 2014 A1
20140006354 Parkison Jan 2014 A1
20140006565 Muscariello Jan 2014 A1
20140029445 Hui Jan 2014 A1
20140032714 Liu Jan 2014 A1
20140033193 Palaniappan Jan 2014 A1
20140040505 Barton Feb 2014 A1
20140040628 Fort Feb 2014 A1
20140047513 vantNoordende Feb 2014 A1
20140074730 Arensmeier Mar 2014 A1
20140075567 Raleigh Mar 2014 A1
20140082135 Jung Mar 2014 A1
20140082661 Krahnstoever Mar 2014 A1
20140089454 Jeon Mar 2014 A1
20140096249 Dupont Apr 2014 A1
20140108313 Heidasch Apr 2014 A1
20140108474 David Apr 2014 A1
20140115037 Liu Apr 2014 A1
20140122587 Petker et al. May 2014 A1
20140129736 Yu May 2014 A1
20140136814 Stark May 2014 A1
20140140348 Perlman May 2014 A1
20140143370 Vilenski May 2014 A1
20140146819 Bae May 2014 A1
20140149733 Kim May 2014 A1
20140237095 Petker May 2014 A1
20140156396 deKozan Jun 2014 A1
20140165207 Engel Jun 2014 A1
20140172783 Suzuki Jun 2014 A1
20140172981 Kim Jun 2014 A1
20140173034 Liu Jun 2014 A1
20140173076 Ravindran Jun 2014 A1
20140192717 Liu Jul 2014 A1
20140195328 Ferens Jul 2014 A1
20140195641 Wang Jul 2014 A1
20140195666 Dumitriu Jul 2014 A1
20140214942 Ozonat Jul 2014 A1
20140233575 Xie Aug 2014 A1
20140237085 Park Aug 2014 A1
20140245359 DeFoy Aug 2014 A1
20140254595 Luo Sep 2014 A1
20140280823 Varvello Sep 2014 A1
20140281489 Peterka Sep 2014 A1
20140281505 Zhang Sep 2014 A1
20140282816 Xie Sep 2014 A1
20140289325 Solis Sep 2014 A1
20140289790 Wilson Sep 2014 A1
20140298248 Kang Oct 2014 A1
20140314093 You Oct 2014 A1
20140337276 Iordanov Nov 2014 A1
20140365550 Jang Dec 2014 A1
20150006896 Franck Jan 2015 A1
20150018770 Baran Jan 2015 A1
20150032892 Narayanan Jan 2015 A1
20150033365 Mellor Jan 2015 A1
20150039890 Khosravi Feb 2015 A1
20150063802 Bahadur Mar 2015 A1
20150089081 Thubert Mar 2015 A1
20150095481 Ohnishi Apr 2015 A1
20150095514 Yu Apr 2015 A1
20150120663 LeScouarnec Apr 2015 A1
20150169758 Assom Jun 2015 A1
20150188770 Naiksatam Jul 2015 A1
20150195149 Vasseur Jul 2015 A1
20150207633 Ravindran Jul 2015 A1
20150207864 Wilson Jul 2015 A1
20150270957 Uzun Sep 2015 A1
20150279348 Cao Oct 2015 A1
20150349961 Mosko Dec 2015 A1
20150372903 Hui Dec 2015 A1
20150381546 Mahadevan Dec 2015 A1
20160021170 Mosko Jan 2016 A1
20160021172 Mahadevan Jan 2016 A1
20160224799 Uzun Aug 2016 A1
20160285671 Rangarajan Sep 2016 A1
20170308681 Gould Oct 2017 A1
Foreign Referenced Citations (21)
Number Date Country
1720277 Jun 1967 DE
19620817 Nov 1997 DE
0295727 Dec 1988 EP
0757065 Jul 1996 EP
1077422 Feb 2001 EP
1384729 Jan 2004 EP
2120402 Nov 2009 EP
2120419 Nov 2009 EP
2124415 Nov 2009 EP
2214357 Aug 2010 EP
2323346 May 2011 EP
2991254 Mar 2016 EP
03005288 Jan 2003 WO
03042254 May 2003 WO
03049369 Jun 2003 WO
03091297 Nov 2003 WO
2007113180 Oct 2007 WO
2007144388 Dec 2007 WO
2011049890 Apr 2011 WO
2013123410 Aug 2013 WO
2015084327 Jun 2015 WO
Non-Patent Literature Citations (170)
Entry
Reaz Ahmed et al, Route: A Name based Routing Scheme for Information Centric Networks, IEEE, 2013.
Jun Kurihara et al, An Encryption-Based Access Control Framework for COntent-Centric Networking, IFIP Networking Conference, 2015.
Marc Mosko et al, All-In-One Streams for Content Centric Networks, ICNS conference, 2015.
Reaz Ahmed et al, Route: A Name based Routing Scheme for Information Centric Networks, IEEE (Year: 2013).
Jun Kurihara et al, An Encryption-Based Access Control Framework for COntent-Centric Networking, IFIP Networking Conference (Year: 2015).
Jacobson, Van et al., “Content-Centric Networking, Whitepaper Describing Future Assurable Global Networks”, Palo Alto Research Center, Inc., Jan. 30, 2007, pp. 1-9.
Koponen, Teemu et al., “A Data-Oriented (and Beyond) Network Architecture”, SIGCOMM '07, Aug. 27-31, 2007, Kyoto, Japan, XP-002579021, p. 181-192.
Jacobson, Van et al. ‘VoCCN: Voice Over Content-Centric Networks.’ Dec. 1, 2009. ACM ReArch'09.
Rosenberg, J. “Interactive Connectivity Establishment (ICE): A Protocol for Network Address Translator (NAT) Traversal for Offer/Answer Protocols”, Apr. 2010, pp. 1-117.
Shih, Eugene et al., ‘Wake on Wireless: An Event Driven Energy Saving Strategy for Battery Operated Devices’, Sep. 23, 2002, pp. 160-171.
Fall, K. et al., “DTN: an architectural retrospective”, Selected areas in communications, IEEE Journal on, vol. 28, No. 5, Jun. 1, 2008, pp. 828-835.
Gritter, M. et al., ‘An Architecture for content routing support in the Internet’, Proceedings of 3rd Usenix Symposium on Internet Technologies and Systems, 2001, pp. 37-48.
“CCNx,” http://ccnx.org/. downloaded Mar. 11, 2015.
“Content Delivery Network”, Wikipedia, Dec. 10, 2011, http://en.wikipedia.org/w/index.php?title=Content_delivery_network&oldid=465077460.
“Digital Signature” archived on Aug. 31, 2009 at http://web.archive.org/web/20090831170721/http://en.wikipedia.org/wiki/Digital_signature.
“Introducing JSON,” http://www.json.org/. downloaded Mar. 11, 2015.
“Microsoft PlayReady,” http://www.microsoft.com/playready/.downloaded Mar. 11, 2015.
“Pursuing a pub/sub internet (PURSUIT),” http://www.fp7-pursuit.ew/PursuitWeb/. downloaded Mar. 11, 2015.
“The FP7 4WARD project,” http://www.4ward-project.eu/. downloaded Mar. 11, 2015.
A. Broder and A. Karlin, “Multilevel Adaptive Hashing”, Jan. 1990, pp. 43-53.
Detti, Andrea, et al. “CONET: a content centric inter-networking architecture.” Proceedings of the ACM SIGCOMM workshop on Information-centric networking. ACM, 2011.
A. Wolman, M. Voelker, N. Sharma N. Cardwell, A. Karlin, and H.M. Levy, “On the scale and performance of cooperative web proxy caching,” ACM SIGHOPS Operating Systems Review, vol. 33, No. 5, pp. 16-31, Dec. 1999.
Afanasyev, Alexander, et al. “Interest flooding attack and countermeasures in Named Data Networking.” IFIP Networking Conference, 2013. IEEE, 2013.
Ao-Jan Su, David R. Choffnes, Aleksandar Kuzmanovic, and Fabian E. Bustamante. Drafting Behind Akamai: Inferring Network Conditions Based on CDN Redirections. IEEE/ACM Transactions on Networking {Feb. 2009).
B. Ahlgren et al., ‘A Survey of Information-centric Networking’ IEEE Commun. Magazine, Jul. 2012, pp. 26-36.
“PBC Library-Pairing-Based Cryptography-About,” http://crypto.stanford.edu/pbc. downloaded Apr. 27, 2015.
Bari, MdFaizul, et al. ‘A survey of naming and routing in information-centric networks.’ Communications Magazine, IEEE 50.12 (2012): 44-53.
Baugher, Mark et al., “Self-Verifying Names for Read-Only Named Data”, 2012 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Mar. 2012, pp. 274-279.
Brambley, Michael, A novel, low-cost, reduced-sensor approach for providing smart remote monitoring and diagnostics for packaged air conditioners and heat pumps. Pacific Northwest National Laboratory, 2009.
C. Gentry and A. Silverberg. Hierarchical ID-Based Cryptography. Advances in Cryptology—ASIACRYPT 2002. Springer Berlin Heidelberg (2002).
C.A. Wood and E. Uzun, “Flexible end-to-end content security in CCN,” in Proc. IEEE CCNC 2014, Las Vegas, CA, USA, Jan. 2014.
Carzaniga, Antonio, Matthew J. Rutherford, and Alexander L. Wolf. ‘A routing scheme for content-based networking.’ INFOCOM 2004. Twenty-third Annual Joint Conference of the IEEE Computer and Communications Societies. vol. 2. IEEE, 2004.
Cho, Jin-Hee, Ananthram Swami, and Ray Chen. “A survey on trust management for mobile ad hoc networks.” Communications Surveys & Tutorials, IEEE 13.4 (2011): 562-583.
Compagno, Alberto, et al. “Poseidon: Mitigating interest flooding DDoS attacks in named data networking.” Local Computer Networks (LCN), 2013 IEEE 38th Conference on. IEEE, 2013.
Conner, William, et al. “A trust management framework for service-oriented environments.” Proceedings of the 18th international conference on World wide web. ACM, 2009.
Content Centric Networking Project (CCN) [online], http://ccnx.org/releases/latest/doc/technical/, Downloaded Mar. 9, 2015.
Content Mediator Architecture for Content-aware Networks (COMET) Project [online], http://www.comet-project.org/, Downloaded Mar. 9, 2015.
Boneh et al., “Collusion Resistant Broadcast Encryption With Short Ciphertexts and Private Keys”, 2005.
D. Boneh and M. Franklin. Identity-Based Encryption from the Weil Pairing. Advances in Cryptology—CRYPTO 2001, vol. 2139, Springer Berlin Heidelberg (2001).
D.K. Smetters, P. Golle, and J.D. Thornton, “CCNx access control specifications,” PARC, Tech. Rep., Jul. 2010.
Dabirmoghaddam, Ali, Maziar Mirzazad Barijough, and J. J. Garcia-Luna-Aceves. ‘Understanding optimal caching and opportunistic caching at the edge of information-centric networks.’ Proceedings of the 1st international conference on Information-centric networking. ACM, 2014.
Detti et al., “Supporting the Web with an information centric network that routes by name”, Aug. 2012, Computer Networks 56, pp. 3705-3702.
Dijkstra, Edsger W., and Carel S. Scholten. ‘Termination detection for diffusing computations.’ Information Processing Letters 11.1 (1980): 1-4.
Dijkstra, Edsger W., Wim HJ Feijen, and A_J M. Van Gasteren. “Derivation of a termination detection algorithm for distributed computations.” Control Flow and Data Flow: concepts of distributed programming. Springer Berlin Heidelberg, 1986. 507-512.
E. Rescorla and N. Modadugu, “Datagram transport layer security,” IETF RFC 4347, Apr. 2006.
E.W. Dijkstra, W. Feijen, and A.J.M. Van Gasteren, “Derivation of a Termination Detection Algorithm for Distributed Computations,” Information Processing Letter, vol. 16, No. 5, 1983.
Fayazbakhsh, S. K., Lin, Y., Tootoonchian, A., Ghodsi, A., Koponen, T., Maggs, B., & Shenker, S. {Aug. 2013). Less pain, most of the gain: Incrementally deployable ICN. In ACM SIGCOMM Computer Communication Review (vol. 43, No. 4, pp. 147-158). ACM.
Anteniese et al., “Improved Proxy Re-Encryption Schemes with Applications to Secure Distributed Storage”, 2006.
G. Tyson, S. Kaune, S. Miles, Y. El-Khatib, A. Mauthe, and A. Taweel, “A trace-driven analysis of caching in content-centric networks,” in Proc. IEEE ICCCN 2012, Munich, Germany, Jul.-Aug. 2012, pp. 1-7.
G. Wang, Q. Liu, and J. Wu, “Hierarchical attribute-based encryption for fine-grained access control in cloud storage services,” in Proc. ACM CCS 2010, Chicago, IL, USA, Oct. 2010, pp. 735-737.
G. Xylomenos et al., “A Survey of Information-centric Networking Research,” IEEE Communication Surveys and Tutorials, Jul. 2013.
Garcia, Humberto E., Wen-Chiao Lin, and Semyon M. Meerkov. “A resilient condition assessment monitoring system.” Resilient Control Systems (ISRCS), 2012 5th International Symposium on. IEEE, 2012.
Garcia-Luna-Aceves, Jose J. ‘A unified approach to loop-free routing using distance vectors or link states.’ ACM SIGCOMM Computer Communication Review. vol. 19. No. 4. ACM, 1989.
Garcia-Luna-Aceves, Jose J. ‘Name-Based Content Routing in Information Centric Networks Using Distance Information’ Proc ACM ICN 2014, Sep. 2014.
Ghali, Cesar, GeneTsudik, and Ersin Uzun. “Needle in a Haystack: Mitigating Content Poisoning in Named-Data Networking.” Proceedings of NDSS Workshop on Security of Emerging Networking Technologies (SENT). 2014.
Ghodsi, Ali, et al. “Information-centric networking: seeing the forest for the trees.” Proceedings of the 10th ACM Workshop on Hot Topics in Networks. ACM, 2011.
Ghodsi, Ali, et al. “Naming in content-oriented architectures.” Proceedings of the ACM SIGCOMM workshop on Information-centric networking. ACM, 2011.
Gupta, Anjali, Barbara Liskov, and Rodrigo Rodrigues. “Efficient Routing for Peer-to-Peer Overlays.” NSDI. vol. 4. 2004.
Xiong et al., “CloudSeal: End-to-End Content Protection in Cloud-based Storage and Delivery Services”, 2012.
Heckerman, David, John S. Breese, and Koos Rommelse. “Decision-Theoretic Troubleshooting.” Communications of the ACM. 1995.
Heinemeier, Kristin, et al. “Uncertainties in Achieving Energy Savings from HVAC Maintenance Measures in the Field.” ASHRAE Transactions 118.Part 2 {2012).
Herlich, Matthias et al., “Optimizing Energy Efficiency for Bulk Transfer Networks”, Apr. 13, 2010, pp. 1-3, retrieved for the Internet: URL:http://www.cs.uni-paderborn.de/fileadmin/informationik/ag-karl/publications/miscellaneous/optimizing.pdf (retrieved on Mar. 9, 2012).
Hoque et al., ‘NLSR: Named-data Link State Routing Protocol’, Aug. 12, 2013, ICN 2013, pp. 15-20.
https://code.google.com/p/ccnx-trace/.
I. Psaras, R.G. Clegg, R. Landa, W.K. Chai, and G. Pavlou, “Modelling and evaluation of CCN-caching trees,” in Proc. IFIP Networking 2011, Valencia, Spain, May 2011, pp. 78-91.
Intanagonwiwat, Chalermek, Ramesh Govindan, and Deborah Estrin. ‘Directed diffusion: a scalable and robust communication paradigm for sensor networks.’ Proceedings of the 6th annual international conference on Mobile computing and networking. ACM, 2000.
J. Aumasson and D. Bernstein, “SipHash: a fast short-input PRF”, Sep. 18, 2012.
J. Bethencourt, A, Sahai, and B. Waters, ‘Ciphertext-policy attribute-based encryption,’ in Proc. IEEE Security & Privacy 2007, Berkeley, CA, USA, May 2007, pp. 321-334.
J. Hur, “Improving security and efficiency in attribute-based data sharing,” IEEE Trans. Knowledge Data Eng., vol. 25, No. 10, pp. 2271-2282, Oct. 2013.
J. Shao and Z. Cao. CCA-Secure Proxy Re-Encryption without Pairings. Public Key Cryptography. Springer Lecture Notes in Computer Sciencevol. 5443 (2009).
V. Jacobson et al., ‘Networking Named Content,’ Proc. IEEE CoNEXT '09, Dec. 2009.
Jacobson et al., “Custodian-Based Information Sharing,” Jul. 2012, IEEE Communications Magazine: vol. 50 Issue 7 (p. 3843).
Ji, Kun, et al. “Prognostics enabled resilient control for model-based building automation systems.” Proceedings of the 12th Conference of International Building Performance Simulation Association. 2011.
K. Liang, L. Fang, W. Susilo, and D.S. Wong, “A Ciphertext-policy attribute-based proxy re-encryption with chosen-ciphertext security,” in Proc. INCoS 2013, Xian, China, Sep. 2013, pp. 552-559.
Katipamula, Srinivas, and Michael R. Brambley. “Review article: methods for fault detection, diagnostics, and prognostics for building systemsa review, Part I.” HVAC&R Research 11.1 (2005): 3-25.
Katipamula, Srinivas, and Michael R. Brambley. “Review article: methods for fault detection, diagnostics, and prognostics for building systemsa review, Part II.” HVAC&R Research 11.2 (2005): 169-187.
L. Wang et al., ‘OSPFN: An OSPF Based Routing Protocol for Named Data Networking,’ Technical Report NDN-0003, 2012.
L. Zhou, V. Varadharajan, and M. Hitchens, “Achieving secure role-based access control on encrypted data in cloud storage,” IEEE Trans. Inf. Forensics Security, vol. 8, No. 12, pp. 1947-1960, Dec. 2013.
Li, Wenjia, Anupam Joshi, and Tim Finin. “Coping with node misbehaviors in ad hoc networks: A multi-dimensional trust management approach.” Mobile Data Management (MDM), 2010 Eleventh International Conference on. IEEE, 2010.
Lopez, Javier, et al. “Trust management systems for wireless sensor networks: Best practices.” Computer Communications 33.9 (2010): 1086-1093.
Gopal et al. “Integrating content-based Mechanisms with hierarchical File systems”, Feb. 1999, University of Arizona, 15 pages.
M. Green and G. Ateniese, “Identity-based proxy re-encryption,” in Proc. ACNS 2007, Zhuhai, China, Jun. 2007, pp. 288-306.
M. Ion, J. Zhang, and E.M. Schooler, “Toward content-centric privacy in ICN: Attribute-based encryption and routing,” in Proc. ACM SIGCOMM ICN 2013, Hong Kong, China, Aug. 2013, pp. 39-40.
M. Naor and B. Pinkas “Efficient trace and revoke schemes,” in Proc. FC 2000, Anguilla, British West Indies, Feb. 2000, pp. 1-20.
M. Nystrom, S. Parkinson, A. Rusch, and M. Scott, “PKCS#12: Personal information exchange syntax v. 1.1,” IETF RFC 7292, K. Moriarty, Ed., Jul. 2014.
M. Parsa and J.J. Garcia-Luna-Aceves, “A Protocol for Scalable Loop-free Multicast Routing.” IEEE JSAC, Apr. 1997.
M. Walfish, H. Balakrishnan, and S. Shenker, “Untangling the web from DNS,” in Proc. USENIX NSDI 2004, Oct. 2010, pp. 735-737.
Mahadevan, Priya, et al. “Orbis: rescaling degree correlations to generate annotated internet topologies.” ACM SIGCOMM Computer Communication Review. vol. 37. No. 4. ACM, 2007.
Mahadevan, Priya, et al. “Systematic topology analysis and generation using degree correlations.” ACM SIGCOMM Computer Communication Review. vol. 36. No. 4. ACM, 2006.
Matocha, Jeff, and Tracy Camp. ‘A taxonomy of distributed termination detection algorithms.’ Journal of Systems and Software 43.3 (1998): 207-221.
Matteo Varvello et al., “Caesar: A Content Router for High Speed Forwarding”, ICN 2012, Second Edition on Information-Centric Networking, New York, Aug. 2012.
McWilliams, Jennifer A., and Iain S. Walker. “Home Energy Article: A Systems Approach to Retrofitting Residential HVAC Systems.” Lawrence Berkeley National Laboratory (2005).
Merindol et al., “An efficient algorithm to enable path diversity in link state routing networks”, Jan. 10, Computer Networks 55 (2011), pp. 1132-1140.
Mobility First Project [online], http://mobilityfirst.winlab.rutgers.edu/, Downloaded Mar. 9, 2015.
Narasimhan, Sriram, and Lee Brownston. “HyDE—A General Framework for Stochastic and Hybrid Modelbased Diagnosis.” Proc. DX 7 (2007): 162-169.
NDN Project [online], http://www.named-data.net/, Downloaded Mar. 9, 2015.
Omar, Mawloud, Yacine Challal, and Abdelmadjid Bouabdallah. “Certification-based trust models in mobile ad hoc networks: A survey and taxonomy.” Journal of Network and Computer Applications 35.1 (2012): 268-286.
P. Mahadevan, E.Uzun, S. Sevilla, and J. Garcia-Luna-Aceves, “CCN-krs: A key resolution service for ccn,” in Proceedings of the 1st International Conference on Information-centric Networking, Ser. INC 14 New York, NY, USA: ACM, 2014, pp. 97-106. [Online]. Available: http://doi.acm.org/10.1145/2660129.2660154.
R. H. Deng, J. Weng, S. Liu, and K. Chen. Chosen-Ciphertext Secure Proxy Re-Encryption without Pairings. CANS. Spring Lecture Notes in Computer Science vol. 5339 (2008).
S. Chow, J. Weng, Y. Yang, and R. Deng. Efficient Unidirectional Proxy Re-Encryption. Progress in Cryptology—AFRICACRYPT 2010. Springer Berlin Heidelberg (2010).
S. Deering, “Multicast Routing in Internetworks and Extended LANs,” Proc. ACM SIGCOMM '88, Aug. 1988.
S. Deering et al., “The PIM architecture for wide-area multicast routing,” IEEE/ ACM Trans, on Networking, vol. 4, No. 2, Apr. 1996.
S. Jahid, P. Mittal, and N. Borisov, “EASiER: Encryption-based access control in social network with efficient revocation,” in Proc. ACM ASIACCS 2011, Hong Kong, China, Mar. 2011, pp. 411-415.
S. Kamara and K. Lauter, “Cryptographic cloud storage,” in Proc. FC 2010, Tenerife, Canary Islands, Spain, Jan. 2010, pp. 136-149.
S. Kumar et al. “Peacock Hashing: Deterministic and Updatable Hashing for High Performance Networking,” 2008, pp. 556-564.
S. Misra, R. Tourani, and N.E. Majd, “Secure content delivery in information-centric networks: Design, implementation, and analyses,” in Proc. ACM SIGCOMM ICN 2013, Hong Kong, China, Aug. 2013, pp. 73-78.
S. Yu, C. Wang, K. Ren, and W. Lou, “Achieving secure, scalable, and fine-grained data access control in cloud computing,” in Proc. IEEE INFOCOM 2010, San Diego, CA, USA, Mar. 2010, pp. 1-9.
S.J. Lee, M. Gerla, and C. Chiang, “On-demand Multicast Routing Protocol in Multihop Wireless Mobile Networks,” Mobile Networks and Applications, vol. 7, No. 6, 2002.
Sandvine, Global Internet Phenomena Report—Spring 2012. Located online at http://www.sandvine.com/downloads/ documents/Phenomenal H 2012/Sandvine Global Internet Phenomena Report 1H 2012.pdf.
Scalable and Adaptive Internet Solutions (SAIL) Project [online], http://sail-project.eu/ Downloaded Mar. 9, 2015.
Schein, Jeffrey, and Steven T. Bushby. A Simulation Study of a Hierarchical, Rule-Based Method for System-Level Fault Detection and Diagnostics in HVAC Systems. US Department of Commerce,[Technology Administration], National Institute of Standards and Technology, 2005.
Shani, Guy, Joelle Pineau, and Robert Kaplow. “A survey of point-based POMDP solvers.” Autonomous Agents and Multi-Agent Systems 27.1 (2013): 1-51.
Sheppard, John W., and Stephyn GW Butcher. “A formal analysis of fault diagnosis with d-matrices.” Journal of Electronic Testing 23.4 (2007): 309-322.
Shneyderman, Alex et al., ‘Mobile VPN: Delivering Advanced Services in Next Generation Wireless Systems’, Jan. 1, 2003, pp. 3-29.
Solis, Ignacio, and J. J. Garcia-Luna-Aceves. ‘Robust content dissemination in disrupted environments.’ proceedings of the third ACM workshop on Challenged networks. ACM, 2008.
Sun, Ying, and Daniel S. Weld. “A framework for model-based repair.” AAAI. 1993.
T. Ballardie, P. Francis, and J. Crowcroft, “Core Based Trees (CBT),” Proc. ACM SIGCOMM '88, Aug. 1988.
T. Dierts, “The transport layer security (TLS) protocol version 1.2,” IETF RFC 5246, 2008.
T. Koponen, M. Chawla, B.-G. Chun, A. Ermolinskiy, K.H. Kim, S. Shenker, and I. Stoica, ‘A data-oriented (and beyond) network architecture,’ ACM SIGCOMM Computer Communication Review, vol. 37, No. 4, pp. 181-192, Oct. 2007.
The Despotify Project (2012). Available online at http://despotify.sourceforge.net/.
V. Goyal, 0. Pandey, A. Sahai, and B. Waters, “Attribute-based encryption for fine-grained access control of encrypted data,” in Proc. ACM CCS 2006, Alexandria, VA, USA, Oct.-Nov. 2006, pp. 89-98.
V. Jacobson, D.K. Smetters, J.D. Thornton, M.F. Plass, N.H. Briggs, and R.L. Braynard, ‘Networking named content,’ in Proc. ACM CoNEXT 2009, Rome, Italy, Dec. 2009, pp. 1-12.
V. K. Adhikari, S. Jain, Y. Chen, and Z.-L. Zhang. Vivisecting Youtube:An Active Measurement Study. In INFOCOM12 Mini-conference (2012).
Verma, Vandi, Joquin Fernandez, and Reid Simmons. “Probabilistic models for monitoring and fault diagnosis.” The Second IARP and IEEE/RAS Joint Workshop on Technical Challenges for Dependable Robots in Human Environments. Ed. Raja Chatila. Oct. 2002.
Vijay Kumar Adhikari, Yang Guo, Fang Hao, Matteo Varvello, Volker Hilt, Moritz Steiner, and Zhi-Li Zhang. Unreeling Netflix: Understanding and Improving Multi-CDN Movie Delivery. In the Proceedings of IEEE INFOCOM 2012 (2012).
Vutukury, Srinivas, and J. J. Garcia-Luna-Aceves. A simple approximation to minimum-delay routing. vol. 29. No. 4. ACM, 1999.
W.-G. Tzeng and Z.-J. Tzeng, “A public-key traitor tracing scheme with revocation using dynamic shares,” in Proc. PKC 2001, Cheju Island, Korea, Feb. 2001, pp. 207-224.
Waldvogel, Marcel “Fast Longest Prefix Matching: Algorithms, Analysis, and Applications”, A dissertation submitted to the Swiss Federal Institute of Technology Zurich, 2002.
Walker, Iain S. Best practices guide for residential HVAC Retrofits. No. LBNL-53592. Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA (US), 2003.
Wang, Jiangzhe et al., “DMND: Collecting Data from Mobiles Using Named Data”, Vehicular Networking Conference, 2010 IEEE, pp. 49-56.
Xylomenos, George, et al. “A survey of information-centric networking research.” Communications Surveys & Tutorials, IEEE 16.2 (2014): 1024-1049.
Yi, Cheng, et al. ‘A case for stateful forwarding plane.’ Computer Communications 36.7 (2013): 779-791.
Yi, Cheng, et al. ‘Adaptive forwarding in named data networking.’ ACM SIGCOMM computer communication review 42.3 (2012): 62-67.
Zahariadis, Theodore, et al. “Trust management in wireless sensor networks.” European Transactions on Telecommunications 21.4 (2010): 386-395.
Zhang, et al., “Named Data Networking (NDN) Project”, http://www.parc.com/publication/2709/named-data-networking-ndn-project.html, Oct. 2010, NDN-0001, PARC Tech Report.
Zhang, Lixia, et al. ‘Named data networking.’ ACM SIGCOMM Computer Communication Review 44.3 {2014): 66-73.
Soh et al., “Efficient Prefix Updates for IP Router Using Lexicographic Ordering and Updateable Address Set”, Jan. 2008, IEEE Transactions on Computers, vol. 57, No. 1.
Beben et al., “Content Aware Network based on Virtual Infrastructure”, 2012 13th ACIS International Conference on Software Engineering.
Biradar et al., “Review of multicast routing mechanisms in mobile ad hoc networks”, Aug. 16, Journal of Network and Computer Applications 35 (2012) 221-229.
D. Trossen and G. Parisis, “Designing and realizing and information-centric Internet,” IEEE Communications Magazing, vol. 50, No. 7, pp. 60-67, Jul. 2012.
Garcia-Luna-Aceves et al., “Automatic Routing Using Multiple Prefix Labels”, 2012, IEEE, Ad Hoc and Sensor Networking Symposium.
Gasti, Paolo et al., ‘DoS & DDoS in Named Data Networking’, 2013 22nd International Conference on Computer Communications and Networks (ICCCN), Aug. 2013, pp. 1-7.
Ishiyama, “On the Effectiveness of Diffusive Content Caching in Content-Centric Networking”, Nov. 5, 2012, IEEE, Information and Telecommunication Technologies (APSITT), 2012 9th Asia-Pacific Symposium.
J. Hur and D.K. Noh, “Attribute-based access control with efficient revocation in data outsourcing systers,” IEEE Trans. Parallel Distrib. Syst, vol. 22, No. 7, pp. 1214-1221, Jul. 2011.
J. Lotspiech, S. Nusser, and F. Pestoni. Anonymous Trust: Digit.
Kaya et al., “A Low Power Lookup Technique for Multi-Hashing Network Applications”, 2006 IEEE Computer Society Annual Symposium on Emerging VLSI Technologies and Architectures, Mar. 2006.
S. Kamara and K. Lauter. Cryptographic Cloud Storage. Financial Cryptography and Data Security. Springer Berlin Heidelberg (2010).
RTMP (2009). Available online at http://wwwimages.adobe.com/www.adobe.com/content/dam/Adobe/en/devnet/rtmp/ pdf/rtmp specification 1.0.pdf.
Hoque et al., “NLSR: Named-data Link State Routing Protocol”, Aug. 12, 2013, ICN'13.
Nadeem Javaid, “Analysis and design of quality link metrics for routing protocols in Wireless Networks”, PhD Thesis Defense, Dec. 15, 2010, Universete Paris-Est.
Wetherall, David, “Active Network vision and reality: Lessons form a capsule-based system”, ACM Symposium on Operating Systems Principles, Dec. 1, 1999. pp. 64-79.
Kulkarni A.B. et al., “Implementation of a prototype active network”, IEEE, Open Architectures and Network Programming, Apr. 3, 1998, pp. 130-142.
Xie et al. “Collaborative Forwarding and Caching in Content Centric Networks”, Networking 2012.
Lui et al. (A TLV-Structured Data Naming Scheme for Content-Oriented Networking, pp. 5822-5827, International Workshop on the Network of the Future, Communications (ICC), 2012 IEEE International Conference on Jun. 10-15, 2012).
Peter Dely et al. “OpenFlow for Wireless Mesh Networks” Computer Communications and Networks, 2011 Proceedings of 20th International Conference on, IEEE, Jul. 31, 2011 (Jul. 31, 2011), pp. 1-6.
Garnepudi Parimala et al “Proactive, reactive and hybrid multicast routing protocols for Wireless Mesh Networks”, 2013 IEEE International Conference on Computational Intelligence and Computing Research, IEEE, Dec. 26, 2013, pp. 1-7.
Tiancheng Zhuang et al. “Managing Ad Hoc Networks of Smartphones”, International Journal of Information and Education Technology, Oct. 1, 2013.
Amadeo et al. “Design and Analysis of a Transport-Level Solution for Content-Centric VANETs”, University “Mediterranea” of Reggio Calabria, Jun. 15, 2013.
Marc Mosko: “CCNx 1.0 Protocol Introduction” Apr. 2, 2014 [Retrieved from the Internet Jun. 8, 2016] http://www.ccnx.org/pubs/hhg/1.1%20CCNx%201.0%20Protocol%20Introduction.pdf *paragraphs [01.3], [002], [02.1], [0003].
Akash Baid et al: “Comparing alternative approaches for networking of named objects in the future Internet”, Computer Communications Workshops (Infocom Wkshps), 2012 IEEE Conference on, IEEE, Mar. 25, 2012, pp. 298-303, *Paragraph [002]* *figure 1*.
Priya Mahadevan: “CCNx 1.0 Tutorial”, Mar. 16, 2014, pp. 1-11, Retrieved from the Internet: http://www.ccnx.org/pubs/hhg/1.2%20CCNx%201.0%20Tutorial.pdf [retrieved on Jun. 8, 2016] *paragraphs [003]-[006], [0011], [0013]* * figures 1,2*.
Marc Mosko et al “All-In-One Streams for Content Centric Networks”, May 24, 2015, retrieved from the Internet: http://www.ccnx.org/pubs/AllinOne.pdf [downloaded Jun. 9, 2016] *the whole document*.
Cesar Ghali et al. “Elements of Trust in Named-Data Networking”, Feb. 13, 2014 Retrieved from the internet Jun. 17, 2016 http://arxiv.org/pdf/1402.3332v5.pdf *p. 5, col. 1* *p. 2, col. 1-2* * Section 4.1; p. 4, col. 2* *Section 4.2; p. 4, col. 2*.
Priya Mahadevan et al. “CCN-KRS”, Proceedings of the 1st International Conference on Information-Centric Networking, Inc. '14, Sep. 24, 2014.
Flavio Roberto Santos Et al. “Funnel: Choking Polluters in BitTorrent File Sharing Communities”, IEEE Transactions on Network and Service Management, IEEE vol. 8, No. 4, Dec. 1, 2011.
International Search Report and Written Opinion in counterpart International Application No. PCT/US2017/038185, dated Sep. 27, 2017, 12 pages.
Ahmed, et al., “αRoute: A Name Based Routing Scheme for Information Centric Networks,” 2013 Proceedings IEEE INFOCOM, Apr. 2013, pp. 90-94.
Kurihara, et al., “An Encryption-Based Access Control Framework for Content-Centric Networking,” 2015 IFIP Networking Conference, May 2015, pp. 1-9.
Mosko, et al., “Secure Fragmentation for Content Centric Networking,” 2015 IEEE 12th International conference on Mobile AD HOC and Sensor Systems, Oct. 2015, 7 pages.
Tourani, et al., “Security, Privacy, and Access Control in Information-Centric Networking: A Survey,” ariv.org, Cornell University Library, Mar. 2016, 35 pages.
Related Publications (1)
Number Date Country
20170366515 A1 Dec 2017 US