End-to-end secure operations using a query matrix

Abstract

Systems and methods for an end-to-end secure operation using a query matrix Q_M having dimensions d×s. Exemplary methods include: extracting a set of term components {T} of the operation using a term generation function; partitioning a range of a keyed hash function H(T) into a set of vectors {c_T}; setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a non-zero bitmask corresponding to element T from the set of term components {T} encrypted using a homomorphic encryption scheme E; and setting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E.

Description

TECHNICAL FIELD

The present technology relates generally to encryption, and more specifically to homomorphic encryption.

BACKGROUND

The approaches described in this section could be pursued but are not necessarily approaches that have previously been conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.

Encryption is the process of encoding a message or information in such a way that only authorized parties can access it and those who are not authorized cannot. Encryption does not by itself prevent interference, but denies the intelligible content to a would-be interceptor. In an encryption scheme, the intended information or message, referred to as plaintext, is encrypted using an encryption algorithm, referred to as a cipher, generating ciphertext that can only be read if decrypted. A cryptosystem is pair (encryption and decryption) of algorithms that take a key and convert plaintext to ciphertext and back.

Encryption is used by militaries and governments to facilitate secret communication. It is also used to protect information within civilian systems. Encryption can be used to protect data “at rest,” such as information stored on computers and storage devices. Encryption is also used to protect data in transit, for example, data being transferred via networks (e.g., the Internet, e-commerce), mobile telephones, Bluetooth devices and bank automatic teller machines (ATMs).

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.

The present disclosure is related to various systems and methods for an end-to-end secure operation using a query matrix Q_M having dimensions d×s. Specifically, a method may comprise: extracting a set of term components {T} of the operation using a term generation function; partitioning a range of a keyed hash function H(T) into a set of vectors {c_T}, where C(H(T))={c_T: c_T being a d-dimensional vector partitioning the range of keyed hash function H(T) into d-many bitwise components}, such that |C(H(T))|=|H(T)|=|{T}|; setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a non-zero bitmask corresponding to element T from the set of term components {T} encrypted using a homomorphic encryption scheme E; and setting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E.

BRIEF DESCRIPTION OF THE DRAWINGS

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

FIG. 1 is a simplified representation of a system for encryption, according to some embodiments.

FIG. 2 is a simplified representation of a system for homomorphic encryption, according to various embodiments.

FIG. 3 is a simplified block diagram of a system for end-to-end secure operations using a query matrix, in accordance with some embodiments.

FIG. 4 is a flow diagram of a method for end-to-end secure queries using a query matrix, in accordance with various embodiments.

FIG. 5 is a flow diagram of a method for producing a query matrix, according to some embodiments.

FIG. 6 is a simplified block diagram of a computing system, according to various embodiments.

DETAILED DESCRIPTION

While this technology is susceptible of embodiment in many different forms, there is shown in the drawings and will herein be described in detail several specific embodiments with the understanding that the present disclosure is to be considered as an exemplification of the principles of the technology and is not intended to limit the technology to the embodiments illustrated. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the technology. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes,” and/or “including,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that like or analogous elements and/or components, referred to herein, may be identified throughout the drawings with like reference characters. It will be further understood that several of the figures are merely schematic representations of the present technology. As such, some of the components may have been distorted from their actual scale for pictorial clarity.

FIG. 1 illustrates system 100 for encryption, according to some embodiments. System 100 can include source system 110, destination system 120, and communications link 130. Source system 110 and destination system 120 can include at least some of the characteristics of computing systems described further in relation to FIG. 6. Source system 110 can include encryption engine 112. Destination system 120 can include decryption engine 122 and process 124. Encryption engine 112, decryption engine 122, and/or process 124 can include any of an application-specific integrated circuit (ASIC), field programmable gate array (FPGA), application-specific standard product (ASSP), an electronic circuit, a processor (shared, dedicated, or group) that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.

Encryption engine 112 can encrypt plaintext A to ciphertext A′ using an encryption algorithm and an encryption key. Decryption engine 122 can decrypt ciphertext A′ to plaintext A using the encryption algorithm and a decryption key.

In symmetric-key encryption schemes, the encryption and decryption keys are the same. In symmetric-key encryption schemes, source system 110 and destination system 120 should have the same key in order to achieve secure communication over communications link 130. Examples of symmetric-key encryption schemes include: Twofish, Serpent, AES (Rijndael), Blowfish, CAST5, Kuznyechik, RC4, 3DES, Skipjack, Safer+/++ (Bluetooth), and IDEA.

In public-key encryption schemes, the encryption key (public key) is published for anyone (e.g., source system 110) to use and encrypt messages. However, only the receiving party (e.g., destination system 120) has access to the decryption key (private key) that enables messages to be read. Examples of public-key encryption schemes include: RSA, ElGamal, Elliptic Curve Cryptography (ECC), and Cramer-Shoup.

Process 124 can be any operation performed (or application which works) on information (e.g., plaintext A). For example, process 124 can be a database search, Internet search, financial transaction, ecommerce transaction, word processing application, spreadsheet application, and the like.

Although depicted as separate systems, source system 110 and destination system 120 can be a single system where ciphertext (encrypted or encoded information) is created, stored, and (subsequently) converted back to plaintext (readable information). Communications link 130 can be various combinations and permutations of wired and wireless networks (e.g., Ethernet, Wi-Fi, Bluetooth, mobile broadband, the Internet, etc.), internal/external computer busses, and the like, such as described in relation to FIG. 6.

FIG. 2 shows system 200 for homomorphic encryption, according to various embodiments. System 200 can include source system 210, destination system 220, and communications link 230. Source system 210 and destination system 220 can include at least some of the characteristics of computing systems described further in relation to FIG. 6. Source system 210 can include encryption engine 212. Destination system 220 can include process 224. Encryption engine 212 and/or process 224 can include any of an application-specific integrated circuit (ASIC), field programmable gate array (FPGA), application-specific standard product (ASSP), an electronic circuit, a processor (shared, dedicated, or group) that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality.

Encryption engine 212 can encrypt plaintext B to ciphertext B′ using a homomorphic encryption algorithm and an encryption key. Homomorphic encryption is a form of encryption in which a certain algebraic operation (generally referred to as addition or multiplication) performed on plaintext is equivalent to another operation performed on ciphertext. Homomorphic encryption algorithms can be partially homomorphic (exhibits either additive or multiplicative homomorphism, or an unlimited number addition or multiplication operations and a limited number of multiplication or addition operations) or fully homomorphic (exhibits both additive and multiplicative homomorphism). For example, in partially homomorphic encryption schemes, multiplication in ciphertext is equal to addition of the same values in plaintext.

Examples of partially homomorphic cryptosystems include: RSA (multiplicative homomorphism), ElGamal (multiplicative homomorphism), and Paillier (additive homomorphism). Other partially homomorphic cryptosystems include the Okamoto-Uchiyama, Naccache-Stern, Damgård-Jurik, Sander-Young-Yung, Boneh-Goh-Nissim, and Ishai-Paskin cryptosystems. Examples of fully homomorphic cryptosystems include: the Brakerski-Gentry-Vaikuntanathan, Brakerski's scale-invariant, NTRU-based, and Gentry-Sahai-Waters (GSW) cryptosystems.

Process 224 can be an operation performed (or application which works) on homomorphically encrypted information (e.g., ciphertext B′) such that decrypting the result of the operation is the same as the result of some operation performed on the corresponding plaintext (e.g., plaintext B). For example, a homomorphically encrypted Internet search engine receives encrypted search terms and compare them with an encrypted index of the web. By way of further non-limiting example, a homomorphically encrypted financial database stored in the cloud allows users to ask how much money an employee earned in a particular time period. However, it would accept an encrypted employee name and output an encrypted answer, avoiding the privacy problems that can plague online services that deal with such sensitive data.

Communications link 230 can be various combinations and permutations of wired and wireless networks (e.g., Ethernet, Wi-Fi, Bluetooth, mobile broadband, the Internet, etc.), internal/external computer busses, and the like, such as described in relation to FIG. 6.

FIG. 3 depicts system 300 for end-to-end secure operations using a query matrix, in accordance with some embodiments. System 300 can include one or more clients 310₁-310_M, one or more servers 320₁-320_N, and communications links 330. One or more clients 310₁-310_M and one or more servers 320₁-320_N can be disposed in same and/or different locations (e.g., offices, data centers, cities, counties, geographic regions, countries, continents, etc.). Additionally or alternatively, one or more clients 310₁-310_M and one or more servers 320₁-320_N can each be in varied computing environments, including shared computing architectures, hybrid architectures, distinct architectures (e.g., cloud computing environments), and combinations thereof. One or more clients 310₁-310_M and one or more servers 320₁-320_N can include any of an application-specific integrated circuit (ASIC), field programmable gate array (FPGA), application-specific standard product (ASSP), an electronic circuit, a processor (shared, dedicated, or group) that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. Additionally or alternatively, one or more clients 310₁-310_M and one or more servers 320₁-320_N can include at least some of the characteristics of computing systems described further in relation to FIG. 6.

A target data source may be in a single server or distributed over multiple servers of one or more servers 320₁-320_N as target data source 322₁-322_N. Target data source 322₁-322_N can be unencrypted (in plaintext form), deterministically encrypted (e.g., RSA), semantically encrypted (e.g., AES), and combinations thereof. When target data source 322₁-322_N is a combination of encrypted and unencrypted fields, each field can be consistently encrypted or unencrypted. For example, when data source 322₁-322_N includes an unencrypted “employee name” field, the employees names are all unencrypted, as opposed to some name names being encrypted and others unencrypted. By way of further non-limiting example, when data source 322₁-322_N includes an encrypted “social security number” field, the social security numbers are all encrypted, as opposed to some social security numbers being encrypted and others unencrypted. Data stored in and/or retrieved from target data source 322₁-322_N can be encrypted and/or decrypted as described in relation to FIG. 1.

Communications links 330 can be various combinations and permutations of wired and wireless networks (e.g., Ethernet, Wi-Fi, Bluetooth, mobile broadband, the Internet, etc.), internal/external computer busses, and the like, such as described in relation to FIG. 6. Although depicted as a single “block,” communications links 330 can be, for example, multiple distinct/separate combinations and permutations of wired and wireless networks, internal/external computer busses, and the like.

In some embodiments, system 300 encrypts a desired query (or analytic) to be executed over target data source 322₁-322_N using a homomorphic encryption scheme, such as described in relation to FIG. 2. For example, system 300 (e.g., one or more clients 310₁-310_M) encrypts the desired query as a homomorphic query matrix (Q_M). Q_M is encrypted and the desired query should not be recoverable without a private key. For example, the private key can be associated with the keyed hash function. By way of further non-limiting example, the private is not necessarily associated with the keyed hash function. Since one or more servers 320₁-320_N do not decrypt the desired query or the encrypted result E(R), one or more servers 320₁-320_N do not have the private key. The Q_M is a new construct for conducting homomorphic queries, providing a secure and (completely) encrypted way to perform a query. In contrast, traditional methods of performing queries over data sources require decryption of the query.

FIG. 4 illustrates a method 400 for end-to-end secure queries using a query matrix, in accordance with various embodiments. System 300 (FIG. 3) can perform method 400. As described in further detail below, each of one or more clients 310₁-310_M can construct a query (a homomorphic query matrix (Q_M)) comprising encrypted query pieces. Some of the encrypted query pieces will result in information coming back and the rest result in information being thrown away. The query is passed on to one or more servers 320₁-320_N. One or more servers 320₁-320_N run each encrypted query piece over a portion of the data in target data source 322₁-322_N, resulting in data pieces that one or more clients 310₁-310_M want (from the query) to be returned to one or more clients 310₁-310_M. One or more clients 310₁-310_M make the resulting data pieces readable. One or more servers 320₁-320_N do not have visibility into what pieces of data are desired (e.g., servers 320₁-320_N receive the operation (such as a query or analytic) and provide the results from the operation in encrypted form). In this way, the operation is secure from end to end.

At step 410, one or more clients 310₁-310_M can receive information about target data source 322₁-322_N from one or more servers 320₁-320_N. The information can include data schemas associated with data in target data source 322₁-322_N. Data schemas can be a structure of a database. For example, the information can include a number of records, fields in each record (e.g., name, telephone number, social security number, etc.), and the like in target data source 322₁-322_N. By way of further non-limiting example, the information can denote whether target data source 322₁-322_N is unencrypted, encrypted, and combinations thereof. When a part of target data source 322₁-322_N is encrypted, one or more clients 310₁-310_M can receive a decryption key—associated with the encryption method used to encrypt the part of target data source 322₁-322_N—to decrypt returned encrypted data.

At step 420, a request for an operation (desired query or analytic) can be received and optionally authenticated. For example, one or more clients 310₁-310_M (FIG. 3) receive and authenticate the request. At step 430, the operation can be encoded as a homomorphic query matrix (Q_M) using homomorphic encryption scheme E. For example, one or more clients 310₁-310_M produce Q_M. Generating Q_M is described further in relation to FIG. 5.

At step 440, Q_M, a keyed hash function, and a term generation function are provided to one or more servers 320₁-320_N (having target data source 322₁-322_N). For example, one or more clients 310₁-310_M send Q_M, a keyed hash function (including its key), and a term generation function to one or more servers 320₁-320_N. The keyed hash function and term generation function can be used to divide data in target data source 322₁-322_N, so the correct records in target data source 322₁-322_N are mapped to the correct encrypted query piece, so the operation can be conducted in the right way. The term generation function can range from straightforward (e.g., retrieve a name field from a certain row of data) to sophisticated (e.g., run fields through a trained machine-learning model and the output is the term).

Optionally at step 440, metadata (e.g., identifying particular data available from target data source 322₁-322_N, specifying how data in target data source 322₁-322_N is divided, fields in data (from target data source 322₁-322_N) to be returned, etc.) is provided by one or more clients 310₁-310_M to one or more servers 320₁-320_N.

At step 450, using techniques of the homomorphic encryption scheme E and the keyed hash function, each of one or more servers 320₁-320_N can extract a set of term components {T} from target data source 322₁-322_N using the term generation function, evaluate Q_M over the set of term components {T}, and produce encrypted result E(R). At step 460, encrypted result E(R) can be provided by one or more servers 320₁-320_N (FIG. 3) and received by one or more clients 310₁-310_M.

At step 470, encrypted result E(R) can be decrypted using the private key associated with Q_M. For example, one or more clients 310₁-310_M can decrypt the encrypted result. Optionally at step 480, the result R can be decrypted using another decryption key associated with the encryption method used to encrypt the underlying data in target data source 322₁-322_N. Since Q_M includes only non-zero entries for terms in the set of term components {T}, the homomorphic properties of the homomorphic encryption scheme ensure that only results corresponding to the non-zero elements of Q_M are present in result R.

FIG. 5 shows method 500 for constructing query matrix (Q_M). Q_M can have dimensions d×s, where s>|{T}|, s>=d, and d divides |H(T))|. At step 510, a set of term components {T} of the desired query can be extracted using the term generation function. For example, if the desired query is a database query for elements in <row:column> pairs, then {T} reflects the selection of these elements from a database (in target data source 322₁-322_N).

At step 520, the range of keyed hash function H(T) is partitioned into a set of vectors {c_T}. H(T)={H(T): T in {T}} denotes the range of keyed hash function H over the set of term elements {T}. C is a mathematical function that partitions the hash of a term into d components. C(H(T))={c_T: c_T is the d-dimensional vector partitioning the range of keyed hash function H(T) into d-many bitwise components}, |C(H(T))|=|H(T)|=|{T}|. For example, if d=3 and H(T)=000001001111, then c_T={c_T[0], c_T[1], c_T[2]}, where c_T[0]=0000, c_T[1]=0100, and c_T[2]=1111. c_T[d−1] should be distinct for all elements in H(T). When c_T[d−1] is not distinct for all elements in H(T), a different keyed hash function can be used and H(T) and C(H(T)) reconstructed.

At step 530, Q_M can be generated using encrypted bitmasks. For example, Q_M is generated using C(H(T)). For j=0, . . . , (d−1) and for m=0, . . . , (s−1), if there exists an element of C(H(T)) such that c_T[j]=m, then let Q_M (j,m)=E(B_j,m) where B_j,m is a non-zero bitmask corresponding to element T and E is the homomorphic encryption scheme such a described in relation to FIG. 2. B_j,m is a non-zero bitmask chosen for entry j,m in the query matrix, which are encrypted with the homomorphic encryption function E to create the entries of the query matrix. Note that both j and m are subscripts to B. Otherwise Q_M (j,m)=E(0) (zero bitmask). In this manner, Q_M contains encryptions of non-zero bitmasks for only the query terms in {T}.

FIG. 6 depicts an exemplary computer system (or computing system) 600 that may be used to implement some embodiments of the present invention. The computer system 600 in FIG. 6 may be implemented in the contexts of the likes of computing systems, networks, servers, or combinations thereof. The computer system 600 in FIG. 6 includes processor unit(s) 610 and main memory 620. Main memory 620 stores, in part, instructions and data for execution by processor unit(s) 610. Main memory 620 stores the executable code when in operation, in this example. The computer system 600 in FIG. 6 further includes a mass data storage 630, portable storage device 640, output devices 650, user input devices 660, a graphics display system 670, and peripheral device(s) 680.

The components shown in FIG. 6 are depicted as being connected via a single bus 690. The components may be connected through one or more data transport means. Processor unit(s) 610 and main memory 620 are connected via a local microprocessor bus, and the mass data storage 630, peripheral device(s) 680, portable storage device 640, and graphics display system 670 are connected via one or more input/output (I/O) buses.

Mass data storage 630, which can be implemented with a magnetic disk drive, solid state drive, or an optical disk drive, is a non-volatile storage device for storing data and instructions for use by processor unit(s) 610. Mass data storage 630 stores the system software for implementing embodiments of the present disclosure for purposes of loading that software into main memory 620.

Portable storage device 640 operates in conjunction with a portable non-volatile storage medium, such as a flash drive, floppy disk, compact disk, digital video disc, or Universal Serial Bus (USB) storage device, to input and output data and code to and from the computer system 600 in FIG. 6. The system software for implementing embodiments of the present disclosure is stored on such a portable medium and input to the computer system 600 via the portable storage device 640.

User input devices 660 can provide a portion of a user interface. User input devices 660 may include one or more microphones, an alphanumeric keypad, such as a keyboard, for inputting alphanumeric and other information, or a pointing device, such as a mouse, a trackball, stylus, or cursor direction keys. User input devices 660 can also include a touchscreen. Additionally, the computer system 600 as shown in FIG. 6 includes output devices 650. Suitable output devices 650 include speakers, printers, network interfaces, and monitors.

Graphics display system 670 include a liquid crystal display (LCD) or other suitable display device. Graphics display system 670 is configurable to receive textual and graphical information and processes the information for output to the display device.

Peripheral device(s) 680 may include any type of computer support device to add additional functionality to the computer system.

The components provided in the computer system 600 in FIG. 6 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 600 in FIG. 6 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, 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 computing system 600 may be implemented as a cloud-based computing environment, such as a virtual machine and/or container operating within a computing cloud. In other embodiments, the computing system 600 may itself include a cloud-based computing environment, where the functionalities of the computing system 600 are executed in a distributed fashion. Thus, the computing system 600, 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 computing system 600, 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, magnetic, and solid-state disks, such as a fixed disk. Volatile media include dynamic memory, such as system random-access memory (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 programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a Flash memory, 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 wired and/or wireless network, including a (wireless) local area network (LAN/WLAN) or a (wireless) wide area network (WAN/WWAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider, wireless Internet provider, and the like).

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.

Aspects of the present technology are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present technology. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

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.

Claims

1. A computer implemented method for an end-to-end secure operation over a communications link using a query matrix Q_M having dimensions d×s, comprising: extracting, by a processor associated with a client, from a query, a set of term components {T} of the operation using a term generation function, the set of term components {T} corresponding to elements in a target data source, the target data source being associated with a server;partitioning, by the processor, a range of a keyed hash function H(T) into a set of vectors {c_T}, where C(H(T))={c_T: c_T being a d-dimensional vector partitioning the range of the keyed hash function H(T) into d-many bitwise components}, such that |C(H(T))|=|H(T)|=|{T}|; andencrypting, by the processor, the query by constructing, based on the query, the query matrix Q_M by: setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a homomorphic encryption scheme E and B j,m being a non-zero bitmask chosen for entry j,m in Q_M (j,m) corresponding to element T from the set of term components {T}; andsetting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E;the query matrix Q_M being provided to the server over the communications link to be run, by the server, over the target data source.

2. The method of claim 1, further comprising: receiving the operation;providing the query matrix Q_M, the term generation function, and the keyed hash function to a server, the server: including a target data source;extracting the set of term components {T} from the target data source using the term generation function; andapplying the query matrix Q_M over the set of term components {T} to produce encrypted result E(R); anddecrypting encrypted result E(R) using a decryption key to produce result R.

3. The method of claim 1, wherein the target data source is at least one of: unencrypted, deterministically encrypted, and semantically encrypted.

4. The method of claim 1, further comprising: decrypting result R using another key when the target data source is encrypted, the another key being associated with an encryption method used to encrypt the target data source.

5. The method of claim 1, wherein the homomorphic encryption scheme E is partially homomorphic.

6. The method of claim 5, wherein the homomorphic encryption scheme E is at least one of RSA, ElGamal, and Paillier cryptosystems.

7. The method of claim 1, wherein the homomorphic encryption scheme E is fully homomorphic.

8. The method of claim 7, wherein the homomorphic encryption scheme E is at least one of Brakerski-Gentry-Vaikuntanathan, Brakerski's scale-invariant, NTRU- based, and Gentry-Sahai-Waters (GSW) cryptosystems.

9. The method of claim 1, wherein the server comprises multiple instances of one or more of a hardware sever, virtual machine, and container, each instance of the multiple instances including a subset of the target data source.

10. The method of claim 1, further comprising: authenticating the operation.

11. A system for an end-to-end secure operation over a communications link using a query matrix Q_M having dimensions d×s, comprising: a client: extracting, by a hardware processor associated with the client, from a query, a set of term components {T} of the operation using a term generation function, the set of term components {T} corresponding to elements in a target data source, the target data source being associated with a server;partitioning, by the processor, a range of a keyed hash function H(T) into a set of vectors {c_T}, where C(H(T))={c_T: c_T being a d-dimensional vector partitioning the range of the keyed hash function H(T) into d-many bitwise components}, such that |C(H(T))|=|H(T)|=|{T}|; andencrypting, by the processor, the query by constructing, based on the query, the query matrix Q_M by: setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a homomorphic encryption scheme E and B j,m being a non-zero bitmask chosen for entry j,m in Q_M (j,m) corresponding to element T from the set of term components {T}; andsetting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E;the query matrix Q_M being provided to the server over the communications link to be run, by the server, over the target data source.

12. The system of claim 11, wherein the client further: receives the operation;provides the query matrix Q_M, the term generation function, and the keyed hash function to a server; anddecrypts encrypted result E(R) using a decryption key to produce result R; and the system further comprises:the server including a target data source, the server: extracting the set of term components {T} from the target data source using the term generation function; andapplying the query matrix Q_M over the set of term components {T} to produce the encrypted result E(R).

13. The system of claim 11, wherein the target data source is at least one of: unencrypted, deterministically encrypted, and semantically encrypted.

14. The system of claim 11, wherein the client further: decrypts result R using another key when the target data source is encrypted, the another key being associated with an encryption method used to encrypt the target data source.

15. The system of claim 11, wherein the homomorphic encryption scheme E is partially homomorphic.

16. The system of claim 15, wherein the homomorphic encryption scheme E is at least one of RSA, ElGamal, and Paillier cryptosystems.

17. The system of claim 11, wherein the homomorphic encryption scheme E is fully homomorphic.

18. The system of claim 17, wherein the homomorphic encryption scheme E is at least one of Brakerski-Gentry-Vaikuntanathan, Brakerski's scale-invariant, NTRU-based, and Gentry-Sahai-Waters (GSW) cryptosystems.

19. The system of claim 11, wherein the server comprises multiple instances of one or more of a hardware sever, virtual machine, and container, each instance of the multiple instances including a subset of the target data source.

20. A system for an end-to-end secure operation over a communications link using a query matrix Q_M having dimensions d×s, comprising computer instructions stored in a computer memory to perform a method comprising: extracting, by a processor associated with a client, from a query, a set of term components {T} of the operation using a term generation function, the set of term components {T} corresponding to elements in a target data source, the target data source being associated with a server; andpartitioning, by the processor, a range of a keyed hash function H(T) into a set of vectors {c_T}, where C(H(T))={c_T: c_T being a d-dimensional vector partitioning the range of the keyed hash function H(T) into d-many bitwise components}, such that |C(H(T))|=|H(T)|=|{T}|;encrypting, by the processor, the query by constructing, based on the query, the query matrix Q_M by: setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a homomorphic encryption scheme E and B j,m being a non-zero bitmask for entry j,m in Q_M (j,m) corresponding to element T from the set of term components {T}; andsetting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E;the query matrix Q_M being provided to the server over the communications link to be run, by the server, over the target data source.