A method and related devices for secure intersection of Internet of Vehicles data

Abstract

The present application provides a method and related devices for secure intersection of vehicle networking data. The method includes: determining sample data and a security coefficient for secure intersection between a vehicle networking platform and at least one other participating platform; using a domestic encryption algorithm based on the security coefficient and the corresponding vehicle VIM code to determine a target data set for secure intersection; determining a data conversion matrix for data security intersection of the other participating platforms corresponding to the target data set; performing one oblivious transfer based on the target data set and the data conversion matrix to generate an intermediate matrix; generating a masked digest of the sample data according to the intermediate matrix; generating N intersection data pairs according to the masked digest; and determining an intersection data set Z for secure intersection between the vehicle networking platform and at least one other participating platform based on the N intersection data pairs. This method only performs one oblivious transfer, which reduces the communication volume and communication duration while ensuring data security, and has a high intersection response efficiency.

Description

Technical Field

[0001] This application relates to the field of information security technology, and in particular, to a method for secure intersection of vehicle networking data and related devices. Background Art

[0002] With the development of information technology, in the field of technologies such as vehicle networking, the demand for data sharing is becoming increasingly strong. As the application fields of data sharing expand, people's requirements for the shared data and its security, legality, and compliance are also getting higher and higher. When conducting secure multi-party computing and federated machine learning on large-scale various data such as vehicle status data and driving data in application scenarios involving privacy data such as government affairs, finance, and intelligent transportation, in conjunction with vehicle networking management departments, it is often necessary to share data based on the basic requirements of legality, compliance, and security. Currently, this implementation process in the industry mostly conducts secure intersection through oblivious transfer technology. When traditional secure intersection technology needs to perform large-scale secure intersection on a large amount of data, it is necessary to execute the extended protocol of oblivious transfer multiple times for data processing. The communication volume during the processing process is huge, resulting in low response efficiency for large-scale secure intersection of vehicle networking data and poor user satisfaction. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method for secure intersection of vehicle networking data and related devices to at least partially solve the above problems.

[0004] In a first aspect, embodiments of this application provide a method for secure intersection of vehicle networking data, which is characterized by including:

[0005] Based on the sample data and security coefficient k for secure intersection between the vehicle networking platform and at least one other participating platform;

[0006] According to the security coefficient k and the vehicle VIM code corresponding to the sample data, use a domestic encryption algorithm to determine the target data set X for secure intersection of the vehicle networking platform;

[0007] Corresponding to the target data set X, determine the data conversion matrix T for secure intersection of the at least one other participating platform;

[0008] Based on the target data set X and the data conversion matrix T, execute 1-out-k oblivious transfer once to generate an intermediate matrix Q;

[0009] According to the intermediate matrix Q, generate a masked digest of the sample data;

[0010] According to the masked digest, the vehicle networking platform generates N intersection data pairs;

[0011] Based on the N intersection data pairs, determine the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform.

[0012] Optionally, in an embodiment of the present application, determining the security factor k for secure intersection between the vehicle networking platform and at least one other participating platform includes: determining the security factor k according to the data volume of the sample data for secure intersection between the vehicle networking platform and at least one other participating platform.

[0013] Optionally, in an embodiment of the present application, according to the security factor k and the vehicle VIM codes corresponding to the sample data, using a domestic encryption algorithm, determining the target data set X for data secure intersection of the vehicle networking platform includes:

[0014] Initialize a random vector r with a length of the security factor k, where r ∈ {0, 1} k ;

[0015] According to the random vector r, perform a low-end alignment process on the sample data of the vehicle networking platform;

[0016] Using the SM3 encryption algorithm, generate vehicle data of the same length of 256 Tbit based on the sample data after the low-end alignment process, and correspondingly generate a 256-bit random number for each piece of vehicle data;

[0017] Based on the data pairs composed of the vehicle data with a length of 256 bits and the corresponding 256-bit random numbers, determine the target data set X for data secure intersection of the vehicle networking platform.

[0018] Optionally, in an embodiment of the present application, corresponding to the target data set X, determining the data conversion matrix T for data secure intersection of the at least one other participating platform includes:

[0019] According to the data volume m of the sample data of the vehicle networking platform, generate a vector i with a corresponding length, where i ∈ {0, 1} m ;

[0020] Through a data sandbox mechanism, according to the vector i with the corresponding length, initialize a random bit matrix corresponding to the data volume and the security factor k, and the random bit matrix is the data conversion matrix T.

[0021] Optionally, in an embodiment of the present application, the data conversion matrix T includes: k pairs of data with a length of n where t a represents the a-th column of the data conversion matrix T, and a ∈ [1, k].

[0022] Optionally, in an embodiment of the present application, based on the target data set X and the data conversion matrix T, perform 1-out-k oblivious transfer once to generate an intermediate matrix Q, including:

[0023] Generate a vector d with a corresponding length according to the target data set and the security coefficient k, and generate a corresponding number of identity public keys according to the SM9 encryption algorithm;

[0024] According to the vector d and the corresponding number of identity public keys, the vehicle networking platform and the at least one other participating platform perform 1-out-k oblivious transfer once, so as to parse and obtain the data with a length of n bits in the data conversion matrix T on the vehicle networking platform, and generate an intermediate matrix Q with n×k bits according to the data with a length of n bits in the data conversion matrix T. The intermediate matrix Q has the following logic:

[0025]

[0026] where q a represents the n-bit vector of the a-th column of Q, and q b represents the k-bit vector of the b-th row of Q.

[0027] Optionally, in an embodiment of the present application, generating a masked digest of the sample data for data sharing by the vehicle networking platform according to the intermediate matrix Q includes:

[0028] Based on the intermediate matrix Q, generate a masked digest H of the sample data for data sharing by the vehicle networking platform based on the SM3 national encryption algorithm n , where the H n has the following logic:

[0029]

[0030] In an implementation manner of the embodiment of the present application, generating N intersection data pairs by the vehicle networking platform according to the masked digest includes:

[0031] Based on the masked digest H n , when b∈{0,n}, τ = 0, and τ = 1, calculate respectively to generate n intersection data pairs

[0032] Optionally, in an embodiment of the present application, determining the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs includes:

[0033] Based on the n intersection data pairs The at least one other participating platform uses the SM3 national cryptographic algorithm, and the at least one other participating platform determines the obtained masked digest H n；

[0034] H n = SM3(b, t b )

[0035] When b ∈ {0, n}, calculate respectively

[0036]

[0037] To determine the intersection data set Z for secure intersection of the vehicle networking platform and the at least one other participating platform.

[0038] In a second aspect, based on the method for secure intersection of vehicle networking data in the first aspect of the present application, an embodiment of the present application further provides a device for secure intersection of vehicle networking data, including:

[0039] A negotiation module, configured to determine sample data and a security factor k for secure intersection of the vehicle networking platform and at least one other participating platform;

[0040] A determination module, configured to use a domestic encryption algorithm according to the security factor k and the vehicle VIM code corresponding to the sample data to determine a target data set X for secure intersection of the vehicle networking platform;

[0041] A calculation module, configured to determine a data conversion matrix T for secure intersection of the at least one other participating platform corresponding to the target data set X;

[0042] An execution module, based on the target data set X and the data conversion matrix T, executes 1-out-k oblivious transfer once to generate an intermediate matrix Q;

[0043] A masking module, configured to generate a masked digest of the sample data according to the intermediate matrix Q;

[0044] An expansion module, configured to generate N intersection data pairs by the vehicle networking platform according to the masked digest;

[0045] An intersection module, configured to determine the intersection data set Z for secure intersection of the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs.

[0046] In a third aspect, an embodiment of the present application further provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements any one of the methods for secure intersection of vehicle networking data as described in the first aspect of the present application.

[0047] An embodiment of the present application provides a method and related devices for secure intersection of vehicle networking data. The method includes: determining sample data and a security coefficient k for secure intersection between the vehicle networking platform and at least one other participating platform; using a domestic encryption algorithm according to the security coefficient and the vehicle VIM code corresponding to the sample data to determine a target data set X for secure data intersection of the vehicle networking platform; corresponding to the target data set, determining a data conversion matrix T for the at least one other participating platform to perform the data secure intersection; based on the target data set X and the data conversion matrix T, performing 1-out-k oblivious transfer once to generate an intermediate matrix Q; generating a masked digest of the sample data for data sharing of the vehicle networking platform according to the intermediate matrix Q; generating N intersection data pairs by the vehicle networking platform according to the masked digest; and determining an intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs. The method for secure intersection of vehicle networking data provided by the present application can ensure the security of data during the large-scale secure sharing of vehicle networking data as long as one oblivious transfer is performed, thereby greatly reducing the communication volume and communication duration during the data sharing and transmission process, with high intersection response efficiency and good user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments described in the embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a flowchart of a method for secure intersection of vehicle networking data provided by an embodiment of the present application;

[0050] Figure 2 It is a schematic structural diagram of a device for secure intersection of vehicle networking data provided by an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art shall fall within the protection scope of the embodiments of the present application.

[0052] It should be understood that the various steps described in the method embodiments of the present application can be executed in different orders and / or executed in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this regard.

[0053] Example 1

[0054] An embodiment of the present application provides a data security intersection method. As Figure 1 shown, Figure 1 is a flowchart of a data security intersection method provided by an embodiment of the present application. The data security intersection method includes:

[0055] S101. Determine the sample data and the security coefficient k for the secure intersection of the vehicle networking platform with at least one other participating platform;

[0056] S102. According to the security coefficient k and the vehicle VIM code corresponding to the sample data, use a domestic encryption algorithm to determine the target data set X for the vehicle networking platform to perform data security intersection;

[0057] S103. Corresponding to the target data set X, determine the data conversion matrix T for the at least one other participating platform to perform data security intersection;

[0058] S104. Based on the target data set X and the data conversion matrix T, perform 1 time of 1-out-k oblivious transfer to generate an intermediate matrix Q;

[0059] S105. Generate a masked digest of the sample data according to the intermediate matrix Q;

[0060] S106. According to the masked digest, the vehicle networking platform generates N intersection data pairs;

[0061] S107. Based on the N intersection data pairs, determine the intersection data set Z for the secure intersection of the vehicle networking platform with the at least one other participating platform.

[0062] Optionally, in an implementation manner of the embodiment of the present application, the determining the security coefficient k for the secure intersection of the vehicle networking platform with at least one other participating platform includes: determining the security coefficient k according to the data volume of the sample data for the secure intersection of the vehicle networking platform with at least one other participating platform.

[0063] Optionally, in an implementation manner of the embodiments of the present application, according to the safety factor k and the vehicle VIM code corresponding to the sample data, a domestic encryption algorithm is used to determine the target data set X for data security intersection of the vehicle networking platform, including: initializing a random vector r with a length of the safety factor k, where r ∈ {0, 1} k ; according to the random vector r, perform a low-end alignment process on the sample data of the vehicle networking platform; use the SM3 encryption algorithm to generate vehicle data of the same length of 256 Tbit according to the sample data after the low-end alignment process, and correspondingly generate a 256-bit random number for each piece of vehicle data; based on the data pair composed of the vehicle data with a length of 256 bits and its corresponding 256-bit random number, determine the target data set X for data security intersection of the vehicle networking platform, where the target data set X has the following logic:

[0064]

[0065] In the above implementation process of the present application, the VIM of the sample data for secure intersection based on the sample data of the vehicle networking platform is used to determine the target data set, so as to realize the asymmetric encryption transmission of the sample data without the support of a trusted third-party platform certificate, while ensuring the security of data transmission and simplifying the complexity of the secure intersection implementation process.

[0066] Optionally, in an implementation manner of the embodiments of the present application, for the corresponding target data set X, determining the data conversion matrix T for data security intersection of the at least one other participating platform includes: generating a vector i with a corresponding length according to the data volume m of the sample data of the vehicle networking platform, where i ∈ {0, 1} m ; through a data sandbox mechanism, initialize a random bit matrix corresponding to the data volume and the safety factor k according to the vector i with the corresponding length, and the random bit matrix is the data conversion matrix T.

[0067] Optionally, in an implementation manner of the embodiments of the present application, the data conversion matrix T includes: there are k pairs of data with a length of n where t a represents the a-th column of the data conversion matrix T, and a ∈ [1, k].

[0068] Optionally, in an implementation manner of the embodiments of the present application, based on the target data set X and the data conversion matrix T, performing 1 time of 1-out-k oblivious transfer to generate an intermediate matrix Q includes: generating K selected bit positions d1,..., d a …, d k, to form a vector d of corresponding length, and according to the SM9 encryption algorithm, generate the corresponding number of identity public keys Key1, ……, Key k ; According to the vector d and the corresponding number of identity public keys Key1, ……, Key k , the vehicle networking platform and the at least one other participating platform perform 1-out-k oblivious transfer once to parse and obtain the data of length n bits in the data conversion matrix T at the vehicle networking platform, and generate an intermediate matrix Q of n×k bits according to the data of length n bits in the data conversion matrix T. The intermediate matrix Q has the following logic:

[0069]

[0070] where q a represents the n-bit vector of the a-th column of Q, and q b represents the k-bit vector of the b-th row of Q.

[0071] Optionally, in an implementation manner of the embodiment of the present application, the generating the masked summary of the sample data for data sharing by the vehicle networking platform according to the intermediate matrix Q includes: based on the intermediate matrix Q, using the SM3 national cryptography algorithm, generating n masked summaries H n corresponding to the sample data for secure intersection by the vehicle networking platform, where the H n has the following logic:

[0072]

[0073] Optionally, in an implementation manner of the embodiment of the present application, the vehicle networking platform generating n intersection data pairs according to the masked summary includes:

[0074] Based on the masked summary H n , when b∈{0,n}, τ = 0, and τ = 1, calculate respectively, to generate n intersection data pairs

[0075] Optionally, in an implementation manner of the embodiment of the present application, the determining the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the n intersection data pairs includes:

[0076] Based on the n intersection data pairs The at least one other participating platform determines the obtained masked summary H n through the SM3 national cryptography algorithm;

[0077] Hn = SM3(b, t b )

[0078] When b ∈ {0, n}, calculate respectively

[0079]

[0080] to determine, according to Z b the intersection data set Z for the secure intersection of the vehicle networking platform and the at least one other participating platform.

[0081] The embodiment of the present application provides a method for secure intersection of vehicle networking data, including: determining the sample data and the security coefficient k for the secure intersection of the vehicle networking platform and at least one other participating platform; using a domestic encryption algorithm according to the security coefficient and the vehicle VIM code corresponding to the sample data to determine the target data set X for the vehicle networking platform to perform data secure intersection; corresponding to the target data set, determining the data conversion matrix T for the at least one other participating platform to perform the data secure intersection; based on the target data set X and the data conversion matrix T, performing 1 time of 1-out-k oblivious transfer to generate an intermediate matrix Q; generating a masked digest of the sample data for the vehicle networking platform to perform data sharing according to the intermediate matrix Q; generating N intersection data pairs for the vehicle networking platform according to the masked digest; and determining the intersection data set Z for the secure intersection of the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs. The method for secure intersection of vehicle networking data provided by the present application can ensure the security of data during the large-scale secure sharing of vehicle networking data as long as one oblivious transfer is performed, thereby greatly reducing the communication volume and communication duration during the data sharing and transmission process, having a high intersection response efficiency and good user satisfaction.

[0082] Embodiment 2:

[0083] Based on the data secure intersection method in the first aspect of the present application, the embodiment of the present application further provides a device for secure intersection of vehicle networking data, as Figure 2 shown Figure 2 is a schematic structural diagram of a device 20 for secure intersection of vehicle networking data provided in Embodiment 2 of the present application. The device 20 for secure intersection of vehicle networking data includes:

[0084] A negotiation module 201, configured to determine the sample data and the security coefficient k for the secure intersection of the vehicle networking platform and at least one other participating platform;

[0085] A determination module 202, configured to use a domestic encryption algorithm according to the security coefficient and the vehicle VIM code corresponding to the sample data to determine the target data set X for the vehicle networking platform to perform data secure intersection;

[0086] A calculation module 203, configured to determine, for the target data set, a data conversion matrix T for the at least one other participating platform to perform data security intersection.

[0087] An execution module 204, configured to perform 1-out-k oblivious transfer once based on the target data set X and the data conversion matrix T to generate an intermediate matrix Q.

[0088] A masking module 205, configured to generate a masked summary of the sample data for data sharing by the vehicle networking platform according to the intermediate matrix Q.

[0089] An extension module 206, configured to generate N intersection data pairs for the vehicle networking platform according to the masked summary.

[0090] An intersection module 207, configured to determine an intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs.

[0091] Optionally, in an implementation manner of the embodiment of the present application, the negotiation module 201 is further configured to determine the security coefficient k according to the data volume of the sample data for secure intersection between the vehicle networking platform and at least one other participating platform.

[0092] Optionally, in an implementation manner of the embodiment of the present application, the determination module 202 is further configured to: initialize a random vector r with a length of the security coefficient, where r ∈ {0, 1} k ; perform low-end alignment on the vehicle networking data according to the random vector r; use the SM3 encryption algorithm to generate vehicle data with the same length of 256 Tbit according to the low-end aligned vehicle networking data, and correspondingly generate a 256-bit random number for each piece of vehicle data; determine the target data set X for data security intersection of the vehicle networking platform according to the data pair composed of the vehicle data with a length of 256 bits and the corresponding 256-bit random number.

[0093] Optionally, in an implementation manner of the embodiment of the present application, the calculation module 203 is further configured to generate a vector i with a corresponding length according to the data volume m of the sample data of the vehicle networking platform for data sharing, where i ∈ {0, 1} m ; initialize a random bit matrix corresponding to the data volume and the security coefficient according to the vector i with the corresponding length based on the data sandbox mechanism, and the random bit matrix is the data conversion matrix T.

[0094] Optionally, in an implementation of the embodiments of the present application, the data conversion matrix T corresponding to the quantity number and the safety factor includes: k pairs of data with a length of n where t a represents the a-th column of the data conversion matrix T, and a ∈ [1, k].

[0095] Optionally, in an implementation of the embodiments of the present application, the execution module 204 is further configured to:

[0096] Generate a vector d with a corresponding length according to the target data set and the safety factor k, and generate an identification public key corresponding to the quantity of the corresponding length according to the SM9 encryption algorithm;

[0097] According to the vector d and the identification public key, the vehicle networking platform and the at least one other participating platform perform 1-out-k oblivious transfer once;

[0098] To parse the bit data in the data conversion matrix T on the vehicle networking platform, and generate an intermediate matrix Q with n×k bits according to the generated, and the intermediate matrix Q has the following logic:

[0099]

[0100] where, q a represents the n-bit vector of the a-th column of Q, and q b represents the k-bit vector of the b-th row of Q.

[0101] Optionally, in an implementation of the embodiments of the present application, the masking module 205 is further configured to

[0102] Generate a mask digest H of the sample data for data sharing by the vehicle networking platform based on the intermediate matrix Q and the SM3 national cryptography algorithm n , where the H n has the following logic:

[0103]

[0104] Optionally, in an implementation of the embodiments of the present application, the extension module 205 is further configured to:

[0105] Based on the mask digest H n , when b ∈ {0, n}, τ = 0, and τ = 1, calculate respectively To generate n intersection data pairs

[0106] Optionally, in an implementation of the embodiments of the present application, the intersection module 207 is further configured to:

[0107] Based on the n intersection data pairs The at least one other participating platform uses the SM3 national cryptographic algorithm, and the at least one other participating platform determines the obtained masked digest Hn;

[0108] H n = SM3(b, t b )

[0109] When b ∈ {0, n}, calculate respectively

[0110]

[0111] To determine the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform.

[0112] An apparatus for secure intersection of vehicle networking data provided by an embodiment of the present application includes: a negotiation setting module for determining sample data and a security coefficient k for secure intersection between the vehicle networking platform and at least one other participating platform; a determination setting module for determining a target data set X for secure data intersection of the vehicle networking platform according to the security coefficient and the vehicle VIM code corresponding to the sample data, using a domestic encryption algorithm; a calculation setting module for determining a data conversion matrix T for secure data intersection of the at least one other participating platform corresponding to the target data set; an execution setting module for performing 1-out-k oblivious transfer once based on the target data set X and the data conversion matrix T to generate an intermediate matrix Q; a masking module for generating a masked digest of the sample data for data sharing of the vehicle networking platform according to the intermediate matrix Q; an extension module for generating N intersection data pairs by the vehicle networking platform according to the masked digest; an intersection module for determining the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs. The method for secure intersection of vehicle networking data provided by the present application can ensure the security of data during the large-scale secure sharing of vehicle networking data as long as one oblivious transfer is performed, thereby greatly reducing the communication volume and communication duration during the data sharing and transmission process, having a high intersection response efficiency and good user satisfaction.

[0113] Embodiment III

[0114] Based on the data security intersection method of Embodiment I of the present application, an embodiment of the present application further provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the data security intersection method as described in any of the above method embodiments of the present application. The data security intersection method includes but is not limited to:

[0115] Determine the sample data and the security coefficient k for the secure intersection of the vehicle networking platform with at least one other participating platform;

[0116] According to the security coefficient k and the vehicle VIM code corresponding to the sample data, use a domestic encryption algorithm to determine the target data set X for the secure intersection of the vehicle networking platform;

[0117] Corresponding to the target data set X, determine the data transformation matrix T for the secure intersection of the at least one other participating platform;

[0118] Based on the target data set X and the data transformation matrix T, perform 1-out-k oblivious transfer once to generate an intermediate matrix Q;

[0119] Generate a masked digest of the sample data according to the intermediate matrix Q;

[0120] According to the masked digest, the vehicle networking platform generates N intersection data pairs;

[0121] Based on the N intersection data pairs, determine the intersection data set Z for the secure intersection of the vehicle networking platform with the at least one other participating platform.

[0122] So far, the present application has described specific embodiments of the present subject matter. Other embodiments are within the scope of the appended claims. In some cases, the acts recited in the claims may be performed in a different order and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain implementations, multitasking and parallel processing may be advantageous.

[0123] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software improvements (improvements to method flows). However, with the development of technology, many method flow improvements today can be regarded as direct improvements to hardware circuit structures. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement to a method flow cannot be implemented using a hardware entity module. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by a user's programming of the device. A designer can program a digital system "integrated" on a single PLD by themselves, without having to ask a chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called a Hardware Description Language (HDL). There is not just one type of HDL, but many, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. Currently, the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also be aware that by simply performing a little logical programming on the method flow using the above-mentioned several hardware description languages and programming it into an integrated circuit, it is easy to obtain a hardware circuit that implements the logical method flow.

[0124] The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, an application specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of the controller include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, it is entirely possible to logically program the method steps to enable the controller to be implemented in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, and embedded microcontrollers to achieve the same function. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or the structures within the hardware component.

[0125] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0126] For the convenience of description, the above devices are described by dividing them into various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0127] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0128] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not preclude the presence of additional identical elements in the process, method, commodity or device comprising the element.

[0129] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, system or computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0130] The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0131] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

[0132] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for securely intersecting vehicle networking data, characterized in that, Including: Determine the sample data and the security coefficient k for the secure intersection between the vehicle networking platform and at least one other participating platform; According to the security coefficient k and the vehicle VIM code corresponding to the sample data, use a domestic encryption algorithm to determine the target data set X for the data security intersection of the vehicle networking platform; Corresponding to the target data set X, determine the data transformation matrix T for the data security intersection of the at least one other participating platform; Based on the target data set X and the data transformation matrix T, perform 1 time of 1-out-k oblivious transfer to generate an intermediate matrix Q; According to the intermediate matrix Q, generate the masked digest of the sample data; According to the masked digest, the vehicle networking platform generates N intersection data pairs; Based on the N intersection data pairs, determine the intersection data set Z for the secure intersection between the vehicle networking platform and the at least one other participating platform; The performing 1 time of 1-out-k oblivious transfer based on the target data set X and the data transformation matrix T to generate an intermediate matrix Q includes: generating a vector d with a corresponding length according to the target data set and the security coefficient k, and generating a corresponding number of identity public keys according to the SM9 encryption algorithm; according to the vector d and the corresponding number of identity public keys, the vehicle networking platform and the at least one other participating platform perform 1 time of 1-out-k oblivious transfer to parse and obtain the data with a length of n bits in the data transformation matrix T at the vehicle networking platform, and generate an intermediate matrix Q with n×k bits according to the data with a length of n bits in the data transformation matrix T. The intermediate matrix Q has the following logic: where q a represents the n-bit vector of the a-th column of Q, and q b represents the k-bit vector of the b-th row of Q. r is a randomly initialized vector of length k of the security coefficient, and r ∈ {0, 1} k ; The data conversion matrix T includes: k pairs of data with a length of n bits where t a represents the a-th column of the data conversion matrix T, a ∈ [1, k]; b ∈ {0, n} Generating a masked digest of sample data for data sharing by the vehicle networking platform according to the intermediate matrix Q includes: generating a masked digest H of sample data for data sharing by the vehicle networking platform based on the intermediate matrix Q and the SM3 national cryptography algorithm n , where the H n has the following logic:

2. The method for secure intersection of vehicle networking data according to claim 1, characterized in that The determining the security coefficient k for the secure intersection between the vehicle networking platform and at least one other participating platform includes: Determine the security coefficient k according to the data volume of the sample data for the secure intersection between the vehicle networking platform and at least one other participating platform.

3. The method for secure intersection of vehicle networking data according to claim 1, characterized in that, According to the security coefficient k and the vehicle VIM code corresponding to the sample data, using a domestic encryption algorithm to determine the target data set X for the data security intersection of the vehicle networking platform includes: Perform a lower bound alignment process on the sample data of the vehicle networking platform according to the random vector r; Using the SM3 encryption algorithm, generate vehicle data with the same length of 256Tbit according to the sample data after the lower bound alignment process, and generate a 256-bit random number for each piece of vehicle data; Based on the data pairs composed of the vehicle data with a length of 256 bits and their corresponding 256-bit random numbers, determine the target data set X for the data security intersection of the vehicle networking platform.

4. The method for secure intersection of vehicle networking data according to claim 1, characterized in that, The corresponding to the target data set X, determining the data transformation matrix T for the data security intersection of the at least one other participating platform includes: Generate a vector \(i\) with a corresponding length according to the data volume \(m\) of the sample data of the vehicle networking platform, where \(i\in\{0,1\}\). m ; Through a data sandbox mechanism, initialize a random bit matrix corresponding to the data volume and the security coefficient k according to the vector i with a corresponding length. The random bit matrix is the data transformation matrix T.

5. The method for secure intersection of vehicle networking data according to claim 1, characterized in that The generating N intersection data pairs by the vehicle networking platform according to the masked digest includes: Based on the masked digest H n , when b ∈ {0, n}, τ = 0, and τ = 1, calculate respectively to generate n intersection data pairs 6. The method for secure intersection of vehicle networking data according to claim 5, wherein Determining the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform based on the N intersection data pairs includes: Based on the n intersection data pairs The at least one other participating platform determines the obtained masked digest H through the SM3 national cryptographic algorithm n； H n = SM3(b, t b ) When b ∈ {0, n}, calculate respectively To determine the intersection data set Z for secure intersection between the vehicle networking platform and the at least one other participating platform.

7. A storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the method for secure intersection of vehicle networking data as described in any one of claims 1-6.

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