Selector derived encryption systems and methods

Information

  • Patent Grant
  • 11601258
  • Patent Number
    11,601,258
  • Date Filed
    Thursday, October 8, 2020
    4 years ago
  • Date Issued
    Tuesday, March 7, 2023
    a year ago
  • Inventors
  • Original Assignees
  • Examiners
    • Shaw; Brian F
    • Yi; Jeongsook
    Agents
    • Carr & Ferrell LLP
Abstract
Example selector derived encryption methods and systems include creating a hashed and encrypted database, as well as performing a query against the hashed and encrypted database using an encrypted selector exchange protocol to prevent the exposure of extraneous data from the hashed and encrypted database.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS

N/A.


TECHNICAL FIELD

This disclosure relates to the technical field of encryption, and more specifically, but not by limitation to systems and methods that prevent unauthorized disclosure of data through the use of selector derived encryption.


SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described in the Detailed Description below. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.


According to one example embodiment of the present disclosure, a method includes generating, by a responder, a hashed and encrypted database from a cleartext database by: encrypting selectors of the cleartext database using a responder key of a commutative encryption scheme, each selector being assigned a bucket identifier; encrypting rows of the cleartext database with responder derived keys generated from the encrypted selectors; grouping the encrypted rows according to bucket identifiers; determining a hash bucket identifier of a query based on a requested selector of a query; and returning at least two encrypted rows corresponding to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector; and performing an encrypted selector exchange protocol that comprises: encrypting the requested selector a first time, by a querier, using a querier key of a commutative encryption scheme; encrypting the requested selector a second time, by the responder, using the responder key to create a twice encrypted selector; receiving, by the querier, the twice encrypted selector; decrypting, by the querier, the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key; and deriving, by the querier, the responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector to recover the cleartext corresponding to the least one encrypted row, the querier being unable to decrypt the at least one encrypted row that does not correspond to the requested selector.


According to one example embodiment of the present disclosure, a method includes determining a hash bucket identifier from a requested selector of a query; obtaining at least two encrypted rows from a hashed and encrypted database that correspond to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector; and performing an encrypted selector exchange protocol that comprises: encrypting the requested selector a first time using a querier key; encrypting the requested selector a second time using a responder key to create a twice encrypted selector; decrypting the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key; deriving the responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector; and recovering cleartext corresponding to the least one encrypted row using the responder derived key, wherein the at least one encrypted row that does not correspond to the requested selector cannot be decrypted using the responder derived key.


According to one example embodiment of the present disclosure, a system includes a responder comprising a processor; and memory for storing instructions, the processor executes the instructions to generate a hashed and encrypted database from a cleartext database as the responder: encrypts selectors of the cleartext database using a responder key, each selector being assigned a bucket identifier; encrypts rows of the cleartext database with responder derived keys generated from the encrypted selectors; groups the encrypted rows according to bucket identifiers; determines a hash bucket identifier of a query based on a requested selector of a query; and returns at least two encrypted rows corresponding to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector.





BRIEF DESCRIPTION OF DRAWINGS

Exemplary embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements.



FIG. 1 is a block diagram of an example environment suitable for practicing methods for secure probabilistic analytics using an encrypted analytics matrix as described herein.



FIG. 2 illustrates an example cleartext database and corresponding process for encrypting selectors of the cleartext database.



FIG. 3 illustrates an example process for encrypting rows of the cleartext database.



FIG. 4 illustrates an example process for grouping the encrypted rows into a hashed and encrypted database.



FIG. 5 is a flow diagram that illustrates the use of a hashed and encrypted database and a query to generate query output.



FIG. 6 illustrates an encrypted selector exchange process.



FIG. 7 is a flowchart of a method of the present disclosure.



FIG. 8 is a flowchart of another method of the present disclosure.



FIG. 9 is a flowchart of yet another method of the present disclosure.



FIG. 10 is a flowchart of another method of the present disclosure.



FIG. 11 is a computer system that can be used to implement various embodiments of the present disclosure.





DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The present disclosure pertains to encryption services and systems, and more particularly to selector derived encryption. Generally, selector derived encryption provides advantages over other encryption techniques and can be used to prevent or mitigate issues that may arise when cleartext data could be inadvertently exposed due to issues such as hash collisions. By way of example, hash collisions may occur when using methods such as hash-based private information retrieval (HPIR). Generally, in HPIR a hashed database is created from a cleartext database. The hashed database is used as an argument in a protocol for private information retrieval. In response to a query, data can be retrieved from the cleartext database using data obtained from the hashed database. When a hash collision occurs, two or more database entries may be returned in response to the query, rather than a single database entry. This may preclude the usage of HPIR in use cases where returning data from hash collisions is undesirable, or prohibited by some policy or regulation.


The systems and methods disclosed herein provide advantages over HPIR by implementing selector derived encryption (SDE) that prevents or mitigates hash collisions. Broadly, SDE utilizes a commutative encryption scheme. In some embodiments, the commutative encryption scheme is deterministic and can be used to encrypt a cleartext database into a hashed and encrypted database. A querier can provide a selector that is used to query the hashed and encrypted database provided by a responder. The responder cannot determine what data were received by the querier. The querier can only receive data that matches their requested selector(s). The combined use of selector(s) and hashed and encrypted database identifies collisions and correspondingly limits inadvertent disclosure of information to the querier. Additional details with respect to the features are provided in greater detail herein with reference to the collective drawings.


Turning now to the drawings, FIG. 1 depicts an illustrative architecture or illustrative architecture 100 in which techniques and structures of the present disclosure may be implemented. The architecture 100 includes a responder 102, a querier 104, and a service provider 106. Generally, each of the components of the architecture 100 can include a computer system that is programmed to perform the methods and operations disclosed herein. The components of the architecture 100 can communicate over a network 108. The network 108 can include any public and/or private network that would be known to one of ordinary skill in the art. To be sure, while the service provider 106 is illustrated as being separate from the responder 102, in some embodiments, the responder 102 can include the service provider 106. However, it will be understood that both the querier 104 and responder 102 each perform respective functions of the methods. When a service provider is not involved, the querier 104 may not send queries directly to the responder 102 as such an operation would be insecure.


In more detail, the responder 102 can create and maintain a hashed and encrypted database 110 that is created based upon a cleartext database 112. The hashed and encrypted database 110 is provided to the service provider 106 as in response to a query from the querier 104. The querier 104 transmits a query comprising a requested selector to the service provider 106 and receives a response from the service provider 106. In some instances, the response includes collision data from the hashed and encrypted database 110, as will be discussed in greater detail herein. In general, only the parts of the collision data that directly correspond to requested selector can be decrypted by the querier 104.


In more detail, the responder 102 can create the hashed and encrypted database 110 by leveraging a commutative encryption scheme. If an encryption function E(k,m) encrypts message m with a secret key k, a commutative encryption scheme satisfies E(a, E(b,m))=E(b, E(a,m)) for any two secret keys a and b. In other words, the commutative encryption scheme allows for the encryption of data with multiple keys and decryption of data with the same keys, applied in any order. The commutative encryption scheme is deterministic, meaning that all encryptions of the same message m with the same key k produce identical ciphertexts. This allows determinism when deriving keys from messages encrypted under this commutative encryption scheme.


Some embodiments use Elliptic-Curve Cryptography (ECC) as a basis for the commutative encryption scheme, but other example schemas include, but are not limited to, Pohlig-Hellman and/or Shamir, Rivest and Aldeman (SRA). The querier 104 and responder 102 each generate a secret key under this scheme. These keys are referred to as responder key R of the responder 102 and a querier key Q of the querier 104.


In an initial process, the responder 102 encrypts each selector in the cleartext database 112 with their responder key R. Referring to FIGS. 1 and 2, the responder 102 extracts a selector for each row (rows 1-40) of the cleartext database 112. The cleartext database 112 includes a plurality of rows and columns (e.g., columns 114 and 116). As part of the query, the querier 104 specifies a function that will generate a selector for each row; this function can use any combination of columns and any deterministic transformations applied to these columns. In the FIGS. 2-6 the selector is constructed only from column 116 (Birthday).


The responder 102 encrypts the data of the column 116 using the responder key R from the commutative encryption scheme. The responder 102 also computes a hash bucket identifier (e.g., Bucket ID) for each entry by applying a hash function to the selector. The hashed and encrypted database includes column 119 that references Bucket IDs and another column 120 that comprises fields that include the encrypted data of the column 116 of the cleartext database 112 created using the responder key R. For example, the value of a field 118 is encrypted and assigned a Bucket ID of 37.


As best illustrated in FIG. 3, the responder 102 can generate responder derived keys (derived keys 1-40). For example, the responder 102 performs an Advanced Encryption Standard (AES) key derivation for each encrypted selector, by applying a cryptographic hash algorithm (for example, SHA256, but many others exist) to each ciphertext to transform each one into a format compatible for use as an AES key. This produces a different derived key for each selector/field in the cleartext database 112. The derived key for each row is then used to encrypt the full row's data. In FIGS. 1 and 3, the responder 102 can generate responder derived keys for each of the entries/fields of the column 120. For example, a responder derived key 122 is used to encrypt the row 1 (associated with Bucket ID 37) of the cleartext database 112 to produce an encrypted row 124. This process is repeated for each row of the cleartext database 112.


The responder 102 can then group the encrypted rows by their Bucket ID to produce the hashed and encrypted database 110, as illustrated in FIG. 4. The hashed and encrypted database 110 includes a collision between two encrypted rows that were both assigned a Bucket ID of ‘3’. These two encrypted rows are illustrated as being grouped together in a group 125. That is, row three of the hashed and encrypted database 110 illustrated in FIG. 4 includes at least two encrypted rows. For example, row three includes the data of group 125 obtained from at least one encrypted row (namely encrypted row 126) that does correspond to the requested selector ‘October 30’, and at least one encrypted row (namely encrypted row 127) that does not correspond to the requested selector ‘October 30’.


In FIGS. 1 and 5, the hashed and encrypted database 110 is used as the responder's input to a PIR protocol 128. Again, the PIR protocol 128 can be managed by the service provider 106 or it can be conducted between the querier and responder directly. The querier's input to PIR protocol 128 includes a hash bucket identifier that is generated using a hash function that is applied to the requested selector. Again, the requested selector ‘October 30’ and computed hash bucket identifier is ‘3’. The querier's input to PIR protocol 128 (i.e. the Bucket IDs of its desired selectors) remains unchanged, but the bucket data it receives contains rows encrypted with responder derived keys. For context, the requested selector is what the querier desires to query against the hashed and encrypted database 110. A selector as referred to above in the creation of the hashed and encrypted database 110 refers to entries or fields in the cleartext database 112.


It will be understood that the responder derived keys have not been transmitted as part of the PIR protocol, so the querier 104 cannot decrypt any of these data, unless the querier 104 receives the corresponding keys as part of an encrypted selector exchange (ESE) protocol described infra.


As best illustrated in FIGS. 1 and 6, the ESE protocol is an additional protocol between the querier 104 and responder 102 that runs in parallel with the PIR protocol. The querier 104 begins by taking each of the selectors (can be one or more selector) the querier 104 is requesting as part of the PIR protocol and encrypting them with its querier key Q. In this example, the query includes a birthday of ‘October 30’, and the querier 104 encrypts these data using the querier key Q into an encrypted selector 130.


The querier 104 then sends the encrypted selector to the responder 102. Note that the responder 102 does not receive the querier key Q, and therefore cannot decrypt the encrypted selector 130. Instead, the responder 102 encrypts the encrypted selector 130 again with its responder key R. The selector is now encrypted under both commutative encryption keys (e.g., the querier key Q and the responder key R) to produce a twice encrypted selector 132.


The responder 102 sends the twice encrypted selector 132 back to the querier 104. The querier 104 decrypts the twice encrypted selector 132 using the querier key Q. The result is the querier's selectors which were encrypted using the responder key R, referred to as the responder encrypted selector 134.


To be sure, the querier 104 learns these values without receiving or being able to learn the responder key R. Similarly, the responder 102 does not receive and is therefore unable to learn the value of the selector.


Next, the querier 104 derives an AES key from the responder encrypted selector 134, which corresponds to the responder derived key that was generated by the responder 102 when generating the encrypted rows of FIG. 3. Because the commutative encryption scheme used in this process is deterministic, the ciphertext the querier 104 now has for the selector is the same ciphertext used by the responder to derive its AES encryption keys for any rows that contain that selector. The querier 104 thus generates a responder derived key 136.


The querier 104 can then follow a similar key derivation process as described supra to obtain the same AES key used by the responder to encrypt cleartext data that contained the specified selector.


The requested selector ‘October 30’ was encrypted with the responder key R, and used to derive the AES key labeled 2 (e.g., derived key 136). The querier 104 can derive this same AES key, which is identical to that which was derived by the responder 102 when the responder created the encrypted row.


Note that the querier cannot derive the AES keys for any other selectors that it did not specify earlier, because it does not have the responder key R. Finally, after the PIR protocol is complete, the querier takes its selector-derived keys and attempts to decrypt each of the encrypted rows returned as part of the PIR protocol. This decryption will fail for any rows that were encrypted with keys the querier has not received. In the example illustration of FIG. 6, the key labeled 2 successfully decrypts the data of the encrypted row 126 which corresponds to (2, Adams, October 30), which corresponds to the requested selector ‘October 30’ and hash bucket identifier ‘3’.


Of note, both the encrypted rows 2 and 40 (corresponding to the encrypted row 126 and encrypted row 127 of FIG. 4, respectively) were returned, due to a collision that occurred when creating the hashed and encrypted database 110. Despite the collision, and the querier possessing both encrypted rows, the data of row 40 cannot be decrypted by the querier 104 because it only has the responder derived key for the encrypted row 126. This means that the querier 104 only receives plaintext data for the rows that contain the selector(s) it is interested in. Any rows that were returned as the result of a hash collision in the hash-based PIR protocol are undecryptable, and the querier 104 can discard them without ever having to worry about their data being present on its system. The querier 104 can then decrypt the encrypted row 126 to recover cleartext 138 of the encrypted row using the responder derived key 136 that was generated by the querier. The cleartext 138 of FIG. 6 corresponds to the cleartext of row 2 of the cleartext database of FIG. 2.


It will be understood that some of the embodiments disclosed herein contemplate avoiding the disclosure of data when collisions occur. However, the systems and methods herein are not so limited. Thus, the methods of querying using selector derived encryption may not always return data that was the subject of a collision. The systems and methods disclosed herein do not require that data returned from the selector derived encryption protocol contain some rows matching the selector and other rows not matching the selector.


For example, a querier can request a selector that is not in the database. For example, the querier can ask for “April 1” and the bucket ID for that is 2. The selector derived encryption algorithm would return no data, and there would be nothing to decrypt. If the bucket ID were 6 instead, it would return some data but none of it would be decryptable.


It is also possible for the querier to ask for a record that is in the database, but for no hash collisions to occur. In that case all of the records returned by the selector derived encryption algorithm would be decryptable. The purpose of SDE is to guard against the possibility of hash collisions.



FIG. 7 is a flowchart of an example method. The method includes aspects of generating a hashed and encrypted database by a responder. The method can include a step 702 of encrypting selectors of a cleartext database using a responder key of a commutative encryption scheme. As noted above, each selector can be assigned a bucket identifier.


Next, the method includes a step 704 of encrypting rows of the cleartext database with responder derived keys generated from the encrypted selectors. The method can include a step 706 of grouping the encrypted rows according to bucket identifiers to finalize the hashed and encrypted database.



FIG. 8 is a flowchart of a method related to querying the hashed and encrypted database created using the method of FIG. 7. The method can include a step 802 of determining a hash bucket identifier of a query based on a requested selector of a query. The method further includes a step 804 of returning at least two encrypted rows corresponding to the hash bucket identifier. As noted above, the at least two encrypted rows include at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector.



FIG. 9 is a flowchart of a method for performing an encrypted selector exchange protocol. The method can be used in combination with the methods of FIGS. 7 and 8 to ensure that the querier can only decrypt the at least one encrypted row that does correspond to the requested selector. The method includes a step 902 of encrypting the requested selector a first time, by a querier, using a querier key. Next, the method can include a step 904 of encrypting the requested selector a second time, by the responder, using the responder key to create a twice encrypted selector. In some embodiments, the method can include a step 906 of receiving, by the querier, the twice encrypted selector, as well as a step 908 of decrypting, by the querier, the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key.


In one embodiment, the method includes a step 910 of deriving, by the querier, the responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector to recover the cleartext corresponding to the least one encrypted row. As noted above, the querier is unable to decrypt the at least one encrypted row that does not correspond to the requested selector.



FIG. 10 is a flowchart of another example method. The method includes a step 1002 of determining a hash bucket identifier from a requested selector of a query. Next, the method includes a step 1004 of obtaining at least two encrypted rows from a hashed and encrypted database that correspond to the hash bucket identifier. To be sure, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector.


The method can include a step 1006 of performing an encrypted selector exchange protocol, which allows the querier to recover cleartext corresponding to the least one encrypted row using the responder derived key. To be sure, the at least one encrypted row that does not correspond to the requested selector cannot be decrypted using the responder derived key.



FIG. 11 is a diagrammatic representation of an example machine in the form of a computer system 1, within which a set of instructions for causing the machine to perform any one or more of the methodologies discussed herein may be executed. In various example embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, a portable music player (e.g., a portable hard drive audio device such as a Moving Picture Experts Group Audio Layer 3 (MP3) player), a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.


The computer system 1 includes a processor or multiple processor(s) 5 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), or both), and a main memory 10 and static memory 15, which communicate with each other via a bus 20. The computer system 1 may further include a video display 35 (e.g., a liquid crystal display (LCD)). The computer system 1 may also include an alpha-numeric input device(s) 30 (e.g., a keyboard), a cursor control device (e.g., a mouse), a voice recognition or biometric verification unit (not shown), a drive unit 37 (also referred to as disk drive unit), a signal generation device 40 (e.g., a speaker), and a network interface device 45. The computer system 1 may further include a data encryption module (not shown) to encrypt data.


The drive unit 37 includes a computer or machine-readable medium 50 on which is stored one or more sets of instructions and data structures (e.g., instructions 55) embodying or utilizing any one or more of the methodologies or functions described herein. The instructions 55 may also reside, completely or at least partially, within the main memory 10 and/or within the processor(s) 5 during execution thereof by the computer system 1. The main memory 10 and the processor(s) 5 may also constitute machine-readable media.


The instructions 55 may further be transmitted or received over a network via the network interface device 45 utilizing any one of a number of well-known transfer protocols (e.g., Hyper Text Transfer Protocol (HTTP)). While the machine-readable medium 50 is shown in an example embodiment to be a single medium, the term “computer-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable medium” shall also be taken to include any medium that is capable of storing, encoding, or carrying a set of instructions for execution by the machine and that causes the machine to perform any one or more of the methodologies of the present application, or that is capable of storing, encoding, or carrying data structures utilized by or associated with such a set of instructions. The term “computer-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media, and carrier wave signals. Such media may also include, without limitation, hard disks, floppy disks, flash memory cards, digital video disks, random access memory (RAM), read only memory (ROM), and the like. The example embodiments described herein may be implemented in an operating environment comprising software installed on a computer, in hardware, or in a combination of software and hardware.


The components provided in the computer system 1 are those typically found in computer systems that may be suitable for use with embodiments of the present disclosure and are intended to represent a broad category of such computer components that are well known in the art. Thus, the computer system 1 can be a personal computer (PC), hand held computer system, telephone, mobile computer system, workstation, tablet, phablet, mobile phone, server, minicomputer, mainframe computer, wearable, or any other computer system. The computer may also include different bus configurations, networked platforms, multi-processor platforms, and the like. Various operating systems may be used including UNIX, LINUX, WINDOWS, MAC OS, PALM OS, QNX ANDROID, IOS, CHROME, TIZEN, and other suitable operating systems.


Some of the above-described functions may be composed of instructions that are stored on storage media (e.g., computer-readable medium). The instructions may be retrieved and executed by the processor. Some examples of storage media are memory devices, tapes, disks, and the like. The instructions are operational when executed by the processor to direct the processor to operate in accord with the technology. Those skilled in the art are familiar with instructions, processor(s), and storage media.


In some embodiments, the computer system 1 may be implemented as a cloud-based computing environment, such as a virtual machine operating within a computing cloud. In other embodiments, the computer system 1 may itself include a cloud-based computing environment, where the functionalities of the computer system 1 are executed in a distributed fashion. Thus, the computer system 1, when configured as a computing cloud, may include pluralities of computing devices in various forms, as will be described in greater detail below.


In general, a cloud-based computing environment is a resource that typically combines the computational power of a large grouping of processors (such as within web servers) and/or that combines the storage capacity of a large grouping of computer memories or storage devices. Systems that provide cloud-based resources may be utilized exclusively by their owners or such systems may be accessible to outside users who deploy applications within the computing infrastructure to obtain the benefit of large computational or storage resources.


The cloud is formed, for example, by a network of web servers that comprise a plurality of computing devices, such as the computer system 1, with each server (or at least a plurality thereof) providing processor and/or storage resources. These servers manage workloads provided by multiple users (e.g., cloud resource customers or other users). Typically, each user places workload demands upon the cloud that vary in real-time, sometimes dramatically. The nature and extent of these variations typically depends on the type of business associated with the user.


It is noteworthy that any hardware platform suitable for performing the processing described herein is suitable for use with the technology. The terms “computer-readable storage medium” and “computer-readable storage media” as used herein refer to any medium or media that participate in providing instructions to a CPU for execution. Such media can take many forms, including, but not limited to, non-volatile media, volatile media and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as a fixed disk. Volatile media include dynamic memory, such as system RAM. Transmission media include coaxial cables, copper wire and fiber optics, among others, including the wires that comprise one embodiment of a bus. Transmission media can also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, a hard disk, magnetic tape, any other magnetic medium, a CD-ROM disk, digital video disk (DVD), any other optical medium, any other physical medium with patterns of marks or holes, a RAM, a PROM, an EPROM, an EEPROM, a FLASHEPROM, any other memory chip or data exchange adapter, a carrier wave, or any other medium from which a computer can read.


Various forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to a CPU for execution. A bus carries the data to system RAM, from which a CPU retrieves and executes the instructions. The instructions received by system RAM can optionally be stored on a fixed disk either before or after execution by a CPU.


Computer program code for carrying out operations for aspects of the present technology may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).


The foregoing detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show illustrations in accordance with exemplary embodiments. These example embodiments, which are also referred to herein as “examples,” are described in enough detail to enable those skilled in the art to practice the present subject matter.


The embodiments can be combined, other embodiments can be utilized, or structural, logical, and electrical changes can be made without departing from the scope of what is claimed. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope is defined by the appended claims and their equivalents. In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one. In this document, the term “or” is used to refer to a nonexclusive “or,” such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. Furthermore, all publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference. In the event of inconsistent usages between this document and those documents so incorporated by reference, the usage in the incorporated reference(s) should be considered supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.


The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present technology has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. Exemplary embodiments were chosen and described in order to best explain the principles of the present technology and its practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.


While various embodiments have been described above, it should be understood that they have been presented by way of example only, and not limitation. The descriptions are not intended to limit the scope of the technology to the particular forms set forth herein. Thus, the breadth and scope of a preferred embodiment should not be limited by any of the above-described exemplary embodiments. It should be understood that the above description is illustrative and not restrictive. To the contrary, the present descriptions are intended to cover such alternatives, modifications, and equivalents as may be included within the spirit and scope of the technology as defined by the appended claims and otherwise appreciated by one of ordinary skill in the art. The scope of the technology should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the appended claims along with their full scope of equivalents.

Claims
  • 1. A method, comprising: generating, by a responder, a hashed and encrypted database from a cleartext database by: encrypting selectors of the cleartext database using a responder key of a commutative encryption scheme, each selector being assigned a bucket identifier;encrypting rows of the cleartext database with responder derived keys generated from the encrypted selectors;grouping the encrypted rows, by the responder, according to bucket identifiers;determining, by the responder, a hash bucket identifier of a query based on a requested selector of a query; andreturning at least two encrypted rows corresponding to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector; andperforming an encrypted selector exchange protocol between a querier and the responder that comprises: encrypting the requested selector a first time, by the querier, using a querier key;encrypting the requested selector a second time, by the responder, using the responder key to create a twice encrypted selector;receiving, by the querier, the twice encrypted selector;decrypting, by the querier, the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key; andderiving, by the querier, the responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector to recover cleartext corresponding to the at least one encrypted row, the querier being unable to decrypt the at least one encrypted row that does not correspond to the requested selector.
  • 2. The method according to claim 1, wherein two or more of the encrypted rows have the same bucket identifier.
  • 3. The method according to claim 1, wherein the querier key and the responder key are identical.
  • 4. The method according to claim 1, wherein the commutative encryption scheme comprises at least one of elliptic curve cryptography, Pohlig-Hellman, and/or Shamir, Rivest and Aldeman.
  • 5. The method according to claim 1, wherein the responder derived keys are created using a hashing function.
  • 6. The method according to claim 5, wherein the hashing function is SHA256.
  • 7. The method according to claim 1, wherein the commutative encryption scheme is deterministic.
  • 8. A method, comprising: determining, by a responder, a hash bucket identifier from a requested selector of a query;obtaining at least two encrypted rows from a hashed and encrypted database that correspond to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision, and at least one encrypted row that does correspond to the requested selector; andperforming an encrypted selector exchange protocol between a querier and the responder that comprises: encrypting the requested selector a first time using a querier key;encrypting the requested selector a second time using a responder key to create a twice encrypted selector;decrypting the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key;deriving a responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector; andrecovering cleartext corresponding to the at least one encrypted row using the responder derived key, wherein the at least one encrypted row that does not correspond to the requested selector cannot be decrypted using the responder derived key.
  • 9. The method according to claim 8, wherein the at least one encrypted row that does not correspond to the requested selector cannot be decrypted using the responder derived key because it was encrypted using a different responder derived key.
  • 10. The method according to claim 8, further comprising generating the hashed and encrypted database by encrypting selectors of a cleartext database using a responder key, each selector being assigned a bucket identifier.
  • 11. The method according to claim 10, further comprising encrypting rows of the cleartext database with responder derived keys generated from the encrypted selectors.
  • 12. The method according to claim 11, further comprising grouping the encrypted rows, by the responder, according to bucket identifiers.
  • 13. The method according to claim 12, further comprising determining a hash bucket identifier of a query based on a requested selector of a query.
  • 14. The method according to claim 8, wherein the responder key and the querier key are part of a commutative encryption scheme.
  • 15. The method according to claim 14, wherein the commutative encryption scheme is deterministic.
  • 16. The method according to claim 8, wherein responder derived keys are created using SHA256.
  • 17. A system, comprising: a responder comprising a processor; and memory for storing instructions, the processor executing the instructions to:generate a hashed and encrypted database from a cleartext database as the responder: encrypts selectors of the cleartext database using a responder key, each selector being assigned a bucket identifier;encrypts rows of the cleartext database with responder derived keys generated from the encrypted selectors;groups the encrypted rows, by the responder, according to bucket identifiers;determines, by the responder, a hash bucket identifier of a query based on a requested selector of a query; andreturns at least one encrypted row that does correspond to the requested selector.
  • 18. The system according to claim 17, wherein the responder is configured to return at least two encrypted rows corresponding to the hash bucket identifier, the at least two encrypted rows comprising at least one encrypted row that does not correspond to the requested selector, but was based on a bucket identifier collision.
  • 19. The system according to claim 17, wherein the responder performs an encrypted selector exchange protocol as the processor executes the instructions to: receive the requested selector that has been encrypted a first time, by a querier, using a querier key;encrypt the requested selector a second time, by the responder, using the responder key to create a twice encrypted selector; andtransmit to the querier, the twice encrypted selector.
  • 20. The system according to claim 19, further comprising the querier, the querier being configured to: decrypt the twice encrypted selector using the querier key to obtain the requested selector that was encrypted with the responder key; andderive a responder derived key used to encrypt the at least one encrypted row that does correspond to the requested selector to recover cleartext corresponding to the at least one encrypted row, the querier being unable to decrypt at least one encrypted row that does not correspond to the requested selector.
US Referenced Citations (204)
Number Name Date Kind
5732390 Katayanagi et al. Mar 1998 A
6178435 Schmookler Jan 2001 B1
6745220 Hars Jun 2004 B1
6748412 Ruehle Jun 2004 B2
6910059 Lu et al. Jun 2005 B2
7712143 Comlekoglu May 2010 B2
7849185 Rockwood Dec 2010 B1
7870398 Perng et al. Jan 2011 B2
7937270 Smaragdis et al. May 2011 B2
8515058 Gentry Aug 2013 B1
8565435 Gentry et al. Oct 2013 B2
8781967 Tehranchi et al. Jul 2014 B2
8832465 Gulati et al. Sep 2014 B2
9059855 Johnson et al. Jun 2015 B2
9094378 Yung et al. Jul 2015 B1
9189411 Mckeen et al. Nov 2015 B2
9215219 Krendelev et al. Dec 2015 B1
9288039 Monet et al. Mar 2016 B1
9491111 Roth et al. Nov 2016 B1
9503432 El Emam et al. Nov 2016 B2
9514317 Martin et al. Dec 2016 B2
9565020 Camenisch et al. Feb 2017 B1
9577829 Roth et al. Feb 2017 B1
9652609 Kang et al. May 2017 B2
9846787 Johnson et al. Dec 2017 B2
9852306 Cash et al. Dec 2017 B2
9942032 Kornaropoulos et al. Apr 2018 B1
9946810 Trepetin et al. Apr 2018 B1
9973334 Hibshoosh et al. May 2018 B2
10027486 Liu Jul 2018 B2
10055602 Deshpande et al. Aug 2018 B2
10073981 Arasu et al. Sep 2018 B2
10075288 Khedr et al. Sep 2018 B1
10120893 Rocamora et al. Nov 2018 B1
10129028 Kamakari et al. Nov 2018 B2
10148438 Evancich et al. Dec 2018 B2
10181049 El Defrawy et al. Jan 2019 B1
10210266 Antonopoulos et al. Feb 2019 B2
10235539 Ito et al. Mar 2019 B2
10255454 Kamara et al. Apr 2019 B2
10333715 Chu et al. Jun 2019 B2
10375042 Chaum Aug 2019 B2
10396984 French et al. Aug 2019 B2
10423806 Cerezo Sanchez Sep 2019 B2
10489604 Yoshino et al. Nov 2019 B2
10496631 Tschudin et al. Dec 2019 B2
10644876 Williams et al. May 2020 B2
10693627 Carr Jun 2020 B2
10721057 Carr Jul 2020 B2
10728018 Williams et al. Jul 2020 B2
10771237 Williams et al. Sep 2020 B2
10790960 Williams et al. Sep 2020 B2
10817262 Carr et al. Oct 2020 B2
10873568 Williams Dec 2020 B2
10880275 Williams Dec 2020 B2
10902133 Williams et al. Jan 2021 B2
10903976 Williams et al. Jan 2021 B2
10972251 Carr Apr 2021 B2
11196540 Williams et al. Dec 2021 B2
11196541 Williams et al. Dec 2021 B2
11290252 Carr Mar 2022 B2
20020032712 Miyasaka et al. Mar 2002 A1
20020073316 Collins et al. Jun 2002 A1
20020104002 Nishizawa et al. Aug 2002 A1
20030037087 Rarick Feb 2003 A1
20030059041 MacKenzie et al. Mar 2003 A1
20030110388 Pavlin et al. Jun 2003 A1
20040167952 Gueron et al. Aug 2004 A1
20040250100 Agrawal Dec 2004 A1
20050008152 MacKenzie Jan 2005 A1
20050076024 Takatsuka et al. Apr 2005 A1
20050259817 Ramzan et al. Nov 2005 A1
20060008080 Higashi et al. Jan 2006 A1
20060008081 Higashi et al. Jan 2006 A1
20070053507 Smaragdis et al. Mar 2007 A1
20070095909 Chaum May 2007 A1
20070140479 Wang et al. Jun 2007 A1
20070143280 Wang et al. Jun 2007 A1
20090037504 Hussain Feb 2009 A1
20090083546 Staddon et al. Mar 2009 A1
20090193033 Ramzan et al. Jul 2009 A1
20090268908 Bikel et al. Oct 2009 A1
20090279694 Takahashi et al. Nov 2009 A1
20090287837 Felsher Nov 2009 A1
20100202606 Almeida Aug 2010 A1
20100205430 Chiou et al. Aug 2010 A1
20100241595 Felsher Sep 2010 A1
20110026781 Osadchy et al. Feb 2011 A1
20110107105 Hada May 2011 A1
20110110525 Gentry May 2011 A1
20110243320 Halevi et al. Oct 2011 A1
20110283099 Nath et al. Nov 2011 A1
20120039469 Mueller et al. Feb 2012 A1
20120054485 Tanaka et al. Mar 2012 A1
20120066510 Weinman Mar 2012 A1
20120201378 Nabeel et al. Aug 2012 A1
20120265794 Niel Oct 2012 A1
20120265797 Niel Oct 2012 A1
20130010950 Kerschbaum Jan 2013 A1
20130051551 El Aimani Feb 2013 A1
20130054665 Felch Feb 2013 A1
20130114811 Boufounos et al. May 2013 A1
20130148868 Troncoso Pastoriza et al. Jun 2013 A1
20130170640 Gentry Jul 2013 A1
20130191650 Balakrishnan et al. Jul 2013 A1
20130195267 Alessio et al. Aug 2013 A1
20130198526 Goto Aug 2013 A1
20130216044 Gentry et al. Aug 2013 A1
20130230168 Takenouchi Sep 2013 A1
20130237242 Oka et al. Sep 2013 A1
20130246813 Mori et al. Sep 2013 A1
20130326224 Yavuz Dec 2013 A1
20130339722 Krendelev et al. Dec 2013 A1
20130339751 Sun et al. Dec 2013 A1
20130346741 Kim et al. Dec 2013 A1
20130346755 Nguyen et al. Dec 2013 A1
20140164758 Ramamurthy et al. Jun 2014 A1
20140189811 Taylor et al. Jul 2014 A1
20140233727 Rohloff et al. Aug 2014 A1
20140281511 Kaushik et al. Sep 2014 A1
20140355756 Iwamura et al. Dec 2014 A1
20150100785 Joye et al. Apr 2015 A1
20150100794 Joye et al. Apr 2015 A1
20150205967 Naedele et al. Jul 2015 A1
20150215123 Kipnis et al. Jul 2015 A1
20150227930 Quigley et al. Aug 2015 A1
20150229480 Joye et al. Aug 2015 A1
20150244517 Nita Aug 2015 A1
20150248458 Sakamoto Sep 2015 A1
20150304736 Lal et al. Oct 2015 A1
20150358152 Ikarashi et al. Dec 2015 A1
20150358153 Gentry Dec 2015 A1
20160004874 Toannidis et al. Jan 2016 A1
20160036826 Pogorelik et al. Feb 2016 A1
20160072623 Joye et al. Mar 2016 A1
20160105402 Soon-Shiong et al. Apr 2016 A1
20160105414 Bringer et al. Apr 2016 A1
20160119346 Chen et al. Apr 2016 A1
20160140348 Nawaz et al. May 2016 A1
20160179945 Lastra Diaz et al. Jun 2016 A1
20160182222 Rane et al. Jun 2016 A1
20160323098 Bathen Nov 2016 A1
20160335450 Yoshino et al. Nov 2016 A1
20160344557 Chabanne et al. Nov 2016 A1
20160350648 Gilad-Bachrach et al. Dec 2016 A1
20170070340 Hibshoosh et al. Mar 2017 A1
20170070351 Yan Mar 2017 A1
20170099133 Gu et al. Apr 2017 A1
20170134158 Pasol et al. May 2017 A1
20170185776 Robinson et al. Jun 2017 A1
20170264426 Joye et al. Sep 2017 A1
20170366562 Zhang et al. Dec 2017 A1
20180091466 Friedman et al. Mar 2018 A1
20180139054 Chu et al. May 2018 A1
20180198601 Laine et al. Jul 2018 A1
20180204284 Cerezo Sanchez Jul 2018 A1
20180212751 Williams et al. Jul 2018 A1
20180212752 Williams et al. Jul 2018 A1
20180212753 Williams Jul 2018 A1
20180212754 Williams et al. Jul 2018 A1
20180212755 Williams et al. Jul 2018 A1
20180212756 Carr Jul 2018 A1
20180212757 Carr Jul 2018 A1
20180212758 Williams et al. Jul 2018 A1
20180212759 Williams et al. Jul 2018 A1
20180212775 Williams Jul 2018 A1
20180212933 Williams Jul 2018 A1
20180224882 Carr Aug 2018 A1
20180234254 Camenisch et al. Aug 2018 A1
20180267981 Sirdey et al. Sep 2018 A1
20180270046 Carr Sep 2018 A1
20180276417 Cerezo Sanchez Sep 2018 A1
20180343109 Koseki et al. Nov 2018 A1
20180349632 Bent et al. Dec 2018 A1
20180359097 Lindell Dec 2018 A1
20180373882 Veugen Dec 2018 A1
20190013950 Becker et al. Jan 2019 A1
20190042786 Williams et al. Feb 2019 A1
20190108350 Bohli et al. Apr 2019 A1
20190158272 Chopra et al. May 2019 A1
20190229887 Ding et al. Jul 2019 A1
20190238311 Zheng Aug 2019 A1
20190251553 Ma et al. Aug 2019 A1
20190251554 Ma et al. Aug 2019 A1
20190253235 Zhang et al. Aug 2019 A1
20190260585 Kawai et al. Aug 2019 A1
20190266282 Mitchell et al. Aug 2019 A1
20190280880 Zhang et al. Sep 2019 A1
20190312728 Poeppelmann Oct 2019 A1
20190327078 Zhang et al. Oct 2019 A1
20190334716 Kocsis et al. Oct 2019 A1
20190349191 Soriente et al. Nov 2019 A1
20190371106 Kaye Dec 2019 A1
20200076578 Ithal Mar 2020 A1
20200134200 Williams et al. Apr 2020 A1
20200150930 Carr et al. May 2020 A1
20200204341 Williams et al. Jun 2020 A1
20200382274 Williams et al. Dec 2020 A1
20200396053 Williams et al. Dec 2020 A1
20210034299 Naqvi Feb 2021 A1
20210034765 Williams et al. Feb 2021 A1
20210105256 Williams Apr 2021 A1
20210409191 Williams et al. Dec 2021 A1
20220006629 Williams et al. Jan 2022 A1
Foreign Referenced Citations (12)
Number Date Country
2887607 Jun 2015 EP
2873186 Mar 2018 EP
5680007 Mar 2015 JP
101386294 Apr 2014 KR
WO2014105160 Jul 2014 WO
WO2015094261 Jun 2015 WO
WO2016003833 Jan 2016 WO
WO2016018502 Feb 2016 WO
WO2018091084 May 2018 WO
WO2018136801 Jul 2018 WO
WO2018136804 Jul 2018 WO
WO2018136811 Jul 2018 WO
Non-Patent Literature Citations (38)
Entry
Fan et al., “Somewhat Practical Fully Homomorphic Encryption”, IACR Cryptol. ePrintArch. 2012, 19 pages.
“Microsoft Computer Dictionary”, pp. 276 and 529, Microsoft Press, 5th Edition, ISBN 0735614954,2002, (Year: 2002), 4 pages.
“Homomorphic encryption”, Wikipedia, May 22, 2021, pages.
“International Search Report” and “Written Opinion of the International Searching Authority,” Patent Cooperation Treaty Application No. PCT/US2018/014535, dated Apr. 19, 2018, 9 pages.
“International Search Report” and “Written Opinion of the International Searching Authority,” Patent Cooperation Treaty Application No. PCT/US2018/014530, dated Apr. 23, 2018, 7 pages.
“International Search Report” and “Written Opinion of the International Searching Authority,” Patent Cooperation Treaty Application No. PCT/US2018/014551, dated Apr. 24, 2018, 8 pages.
Petition to Insitute Derivation Proceeding Pursuant to 35 USC 135; Case No. DER2019-00009, US Patent and Trademark Office Patent Trial and Appeal Board; Jul. 26, 2019, 272 pages. (2 PDFs).
SCAMP Working Paper L29/11, “A Woods Hole Proposal Using Striping,” Dec. 2011, 14 pages.
O'Hara, Michael James, “Shovel-ready Private Information Retrieval,” Dec. 2015, 4 pages.
Carr, Benjamin et al., “Proposed Laughing Owl,” NSA Technical Report, Jan. 5, 2016, 18 pages.
Williams, Ellison Anne et al., “Wideskies: Scalable Private Information Retrieval,” Jun. 8, 2016, 14 pages.
Carr, Benjamin et al., “A Private Stream Search Technique,” NSA Technical Report, Dec. 1, 2015, 18 pages.
Drucker et al., “Paillier-encrypted databases with fast aggregated queries,” 2017 14th IEEE Annual Consumer Communications & Networking Conference (CCNC), Jan. 8-11, 2017, pp. 848-853.
Tu et al., “Processing Analytical Queries over Encrypted Data,” Proceedings of the VLDB Endowment, vol. 6, Issue No. 5, Mar. 13, 2013. pp. 289-300.
Boneh et al., “Private Database Queries Using Somewhat Homomorphic Encryption”, Cryptology ePrint Archive: Report 2013/422, Standford University [online], Jun. 27, 2013, [retrieved on Dec. 9, 2019], 22 pages.
Chen et al., “Efficient Multi-Key Homomorphic Encryption with Packed Ciphertexts with Application to Oblivious Neural Network Inference”, CCS '19 Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, May 19, 2019. pp. 395-412.
Armknecht et al., “A Guide to Fully Homomorphic Encryption” IACR Cryptology ePrint Archive: Report 2015/1192 [online], Dec. 14, 2015, 35 pages.
Bayar et al., “A Deep Learning Approach To Universal Image Manipulation Detection Using A New Convolutional Layer”, IH&MMSec 2016, Jun. 20-22, 2016. pp. 5-10.
Juvekar et al. “Gazelle: A Low Latency Framework for Secure Neural Network Inference”, 27th USENIX Security Symposium, Aug. 15-17, 2018. pp. 1650-1668.
Bösch et al.,“ SOFIR: Securely Outsourced Forensic Recognition,” 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP), IEEE 978-1-4799-2893-4/14, 2014, pp. 2713-2717.
Waziri et al., “Big Data Analytics and Data Security in the Cloud via Fullly Homomorphic Encryption,” World Academy of Science, Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering, vol. 9, No. 3, 2015, pp. 744-753.
Bajpai et al., “A Fully Homomorphic Encryption Implementation on Cloud Computing,” International Journal of Information & Computation Technology, ISSN 0974-2239 vol. 4, No. 8, 2014, pp. 811-816.
Viejo et al., “Asymmetric homomorphisms for secure aggregation in heterogeneous scenarios,” Information Fusion 13, Elsevier B.V., Mar. 21, 2011, pp. 285-295.
Patil et al., “Big Data Privacy Using Fully Homomorphic Non-Deterministic Encryption,” IEEE 7th International Advance Computing Conference, Jan. 5-7, 2017, 15 pages.
Panda et al., “FPGA Prototype of Low Latency BBS PRNG,” IEEE International Symposium on Nanoelectronic and Information Systems, Dec. 2015, pp. 118-123, 7 pages.
Sahu et al., “Implementation of Modular Multiplication for RSA Algorithm,” 2011 International Conference on Communication Systems and Network Technologies, 2011, pp. 112-114, 3 pages.
Drucker et al., “Achieving trustworthy Homomorphic Encryption by combining it with a Trusted Execution Environment,” Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Application (JoWUA), Mar. 2018, pp. 86-99.
Google Scholar, search results for “trusted execution environment database”, 2 pages, Aug. 1, 2020.
PIRK Code Excerpt—QuerierDriver, https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/querier/wideskies/QuerierDriver.java; Jul. 11, 2016; 5 pages.
PIRK Code Excerpt—QuerierDriverCLI, https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/querier/wideskies/QuerierCLI.java; Jul. 11, 2016; 9 pages.
PIRK Code Excerpt—Query; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/query/wideskies/Query.java>; Jul. 11, 2016; 7 pages.
PIRK Code Excerpt—QueryInfo; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/query/wideskies/QueryInfo.java>; Jul. 11, 2016; 4 pages.
PIRK Code Excerpt—ComputeResponse; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/responder/wideskies/spark/ComputeResponse.java>; Jul. 11, 2016; 8 pages.
PIRK Code Excerpt—HashSelectorsAndPartitionData; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/responder/wideskies/spark/HashSelectorsAndPartitionData.java>; Jul. 11, 2016; 2 pages.
PIRK Code Excerpt—HashSelectorsAndFormPartitionsBigInteger; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/responder/wideskies/common/HashSelectorAndPartitionData.java>; Jul. 11, 2016; 3 pages.
PIRK Code Excerpt—QueryUtils; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/query/wideskies/QueryUtils.java>; Jul. 11, 2016; 8 pages.
PIRK Code Excerpt—QuerySchema; [online]; Retreived from the Internet: <URL: https://github.com/apache/incubator-retired-pirk/blob/master/src/main/java/org/apache/pirk/schema/query/QuerySchema.java>; Jul. 11, 2016; 3 pages.
“PIRK Proposal” Apache.org [online], [retreived on Oct. 28, 20]; Retreived from the Internet: <URL:https://cwiki.apache. org/confluence/display/incubator/PirkProposal>; Apr. 10, 2019; 5 pages.
Related Publications (1)
Number Date Country
20220116200 A1 Apr 2022 US