Multi-key data aggregation method for Internet of Vehicles

Abstract

The invention discloses a multi-key data aggregation method oriented to the Internet of Vehicles, relates to the technical field of information security, and ensures that data are transmitted and aggregated in a ciphertext form and encryption operation is executed on a ring by adopting a fully homomorphic encryption technology on a multi-key ring, so that the calculation efficiency and the decryption correctness are improved. According to the method, the data information of each vehicle in the Internet of Vehicles can be protected, unauthorized mechanisms or attackers are prevented from obtaining the data information, and the safety and correctness of the aggregation process are ensured. Even if the gateway or the third party has a part of the secret key, the plaintext data cannot be cracked or acquired; in the whole data processing flow, the confidentiality and the processing efficiency of the data are further improved through multi-layer encryption and homomorphic operation, and effective technical support is provided for the information security of the Internet of Vehicles. According to the method, the data security is enhanced, the processing efficiency is improved, and the method is suitable for an Internet of Vehicles application scene with relatively high requirements on data privacy and security.

Description

Technical Field

[0001] The present invention relates to the field of information security technology, and in particular to a multi-key data aggregation method for an Internet of Vehicles. Background Art

[0002] In order to ultimately provide real-time aggregated data to Internet of Vehicles information technology companies without leaking the data collected by individual vehicles, there are three main technologies to achieve confidentiality: homomorphic encryption, masking, and differential privacy.

[0003] Homomorphic encryption allows aggregation operations to be performed on ciphertext. After decrypting the results of homomorphic operations on all ciphertexts, the same results as the same operations on plaintext can be obtained. This technology effectively ensures the security of data. All vehicle collection data involved is transmitted and aggregated in the form of ciphertext, and homomorphic encryption is provably secure, so no plaintext information is exposed during the entire process. However, in the usual homomorphic encryption scheme, only a single key is supported to participate in the encryption and decryption stages, which can easily be eavesdropped or captured by attackers, and the key can be decrypted to steal user information.

[0004] Masking technology can provide efficient encryption calculations under limited hardware conditions. In this technology, blinding factors are usually used to conceal the data generated by connected vehicles. Only by aggregating all connected vehicles can all blinding factors be offset to obtain the final result. However, due to the security requirement of "one-time one-key", blinding factors need to be constantly updated, which will greatly increase communication and storage overhead.

[0005] Differential privacy can effectively obfuscate data by adding Laplace noise to cover up the real data. However, it is precisely because of the addition of Laplace noise that the differential privacy-based solution has high computational efficiency, but the noise problem will lead to inaccurate decryption of the aggregated results.

[0006] Finally, because in actual situations, the Internet of Vehicles will inevitably fail and they will not be able to submit data on time, which will lead to the failure of the overall aggregation. At this point, the data aggregation scheme used needs to consider its availability. Usually, two technologies, pre-stored blinding factors and secret sharing, are used. The pre-stored blinding factors are mainly operated by the final decryption party. Once a connected vehicle fails to submit data, the decryption party can take out the blinding factor of the user and apply it to its decryption process to obtain the final correct aggregation result. Secret sharing is mainly for the aggregator to reconstruct the blinding factor of the faulty connected vehicle by obtaining the shares stored in other connected vehicles, so that the final aggregation result can be decrypted by reconstructing the ciphertext. However, both of the above technologies have implicit privacy exposure issues and increase communication overhead. Summary of the invention

[0007] In order to solve the above-mentioned problems, the present invention provides a multi-key data aggregation method for the Internet of Vehicles. While assigning different encryption keys to each vehicle, efficient confidential data aggregation can effectively solve the information transmission security problem of intelligent connected vehicles and ensure the information security of vehicle users.

[0008] To achieve the above object, the present invention provides a multi-key data aggregation method for Internet of Vehicles, which specifically includes the following steps: Step S1: The string system generates and initializes the public parameters of LWE and RLWE, including the dimensions, key distribution and error parameters for LWE instance generation and encryption scheme, and the key distribution and error parameters of the public reference string model based on RLWE; Step S2: Randomly generate the private key of the participant according to the public parameters generated by the string system, and generate the corresponding public key, bootstrap key and key conversion key based on the private key; Step S3: The floating point data collected by the connected vehicle is processed into integers and converted into binary form; Step S4: Perform LWE encryption on the processed binary data to generate ciphertext, and send the ciphertext to the gateway; Step S5: After receiving the ciphertext, the gateway uses homomorphic encryption technology to perform homomorphic operations on the ciphertext, specifically including the gateway performing ciphertext expansion and addition operations on the ciphertexts received from multiple participants; performing isomorphic evaluation operations such as XOR, AND, or OR through a multi-key bootstrap algorithm to generate an aggregated ciphertext and send it to the cloud of CNIC, an Internet of Vehicles information technology company. The cloud uses a key conversion key to convert the aggregated ciphertext into a ciphertext that can ultimately be decrypted with a joint key, and returns the final encryption result; Step S6: Decrypt the aggregated ciphertext using the joint key to obtain the final aggregation result.

[0009] Preferably, in step S1, the system parameters are generated Set the fixed parameters as input and call and Two algorithms generate LWE parameters respectively and RLWE parameters , output common parameters ; Specifically include the following steps: S11: Generate a security parameter , The algorithm will be safe parameters As input, it generates the dimensions used in LWE instance generation and encryption schemes , Key Distribution and error parameters ; S12: Vector for gadgets Set the decomposition base and degree ; S13: Initialize and output a LWE common parameter , where the key used in the LWE encryption scheme is From the distribution The gadget vector used when randomly sampling and key transformation in the subsequent aggregation process About The basis decomposition algorithm is to convert the elements Convert to Dimensional vector , the coefficient is and make Minimize, default As part of the input; Generate Parameters The specific steps include: S1-1: Setting the required dimensions in the RLWE encryption scheme , yes The power of S1-2: Setting key distribution exist , and select the error parameter ; S1-3: Set base integer And the decomposition degree is Gadgets Vector ; S1-4: Generate a random vector ; S1-5: Output a RLWE common parameter ,RLWE’s encryption scheme is based on the public reference string CRS model, is part of the input.

[0010] Preferably, in step S2, a private key and a public key are generated , specifically including the following steps: S21: Call Algorithm generation The private key required by each party ; is based on a given LWE key and , open to the entire system from arrive Key conversion key , in Among the participants, for each , No. The items involved and By random sampling and Generate and return ;in ; S22: Call , and These three algorithms generate public keys , Bootstrap Key and key conversion key , returns the user's private key , discloses to all parties and entities a key consisting of a public key, a bootstrap key, and a key conversion key The triple of ; It means from Randomly sample keys ,set up ,from Randomly sampled noise vector , and set the public key to ,run Algorithm to generate RLWE key , and set the public key of the entire system to ; The private key held by the user is used as a key Perform encryption calculations as follows and return the ciphertext : (a) From Random sampling from and error , the output vector ; (b) From Random sampling and , output ciphertext ; in .

[0011] Preferably, in step S3, data processing is performed to input the collected data of the connected vehicle ICV, the data type is floating point data, four decimal places are retained, the floating point data is converted into a processable integer form, and then the integer is converted into a binary number.

[0012] Preferably, in step S4, the data is encrypted For each bit of input , call Encrypt and return to LWE format ,After performing this operation, ICV sends the ciphertext together with the index of the relevant ,participants to the gateway GW; The processed The first participant bit binary data As input, randomly sample and noise , generate ciphertext , which satisfies .

[0013] Preferably, in step S5, the homomorphic operation specifically includes the following steps: S51: performing ciphertext expansion on two ciphertexts at a certain position of two input addends; S52: performing an addition operation on the two expanded ciphertexts; S53: Use To initialize the homomorphic accumulator, use To calculate recursively; S54: Using the key to convert the key Convert the ciphertext into ciphertext that can ultimately be decrypted using the joint key and output the result.

[0014] Preferably, in step S52, due to the length of the bit number, different addition times are performed, and the custom bit adder includes various gate circuits, half adders, carry devices, one-bit adders and fast full bootstrap algorithms, and the code is looped multiple times. The algorithm realizes a multi-bit original code adder connected in series with multiple single-bit original code adders. A single-bit original code adder includes a half adder and a carry device. A half adder consists of two XOR gates, and a carry device consists of three AND gates and two OR gates.

[0015] Preferably, a single-bit original code adder adds the data of two parties, and the gate circuit bootstrap algorithm involved will add the ciphertext generated by the two parties and , a carry information and key triplet As input, the specific situation is as follows: Multi-key bootstrap AND gate :First, Mapping to Ring Generate a message ,calculate ,Will and , as part of the next homomorphic evaluation phase; Multi-key bootstrap OR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Multi-key bootstrap XOR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Half Adder : Called twice , output a single bit without carry as the result of that bit; Carry : Call three times , output the carry information generated by the two addends; One-bit original code adder : Call and Generate The addition result of the bits is output.

[0016] Preferably, in the homomorphic data aggregation operation of step S5, the gateway GW performs ciphertext expansion after receiving the data and calculates the ciphertext after the expansion. , the calculated Transmitted to the public cloud hired by CNIC; After receiving the data transmitted by GW, the cloud employed by CNIC performs bootstrapping and key conversion homomorphic data aggregation operations. Homomorphic addition data aggregation includes the following steps: Step 1: Ciphertext expansion: GW receives the ciphertexts of the two participants sent by the connected vehicle ICV. and and the key triplet corresponding to the participant sent by the key server (KS) , the ciphertext and Expand into and , the extended ciphertext is the joint key The result of encrypting the same information; Step 2: GW uses two extended ciphertexts and calculate , the calculated Transmitted to the public cloud hired by CNIC; Step 3: Bootstrapping: After receiving the data, the cloud ,calculate and , initialize the RLWE type ciphertext ; in ,make ,run For all and Perform recursive calculation , the bootstrap will output for the next step ; Step 4: Key conversion: CNIC employs the cloud to receive ,make for The constant term of is for of The coefficient vector of LWE ciphertext ,make ,run Calculate the final ciphertext , and send the final result to CNIC, where The algorithm will be based on the ciphertext sent by GW in and the conversion key published by KS sequence, for all participants calculate , and let satisfy , returns the ciphertext ,The key conversion algorithm will take the input extended ciphertext and the key conversion key and calculate the ciphertext of the same message under the joint key encryption.

[0017] Preferably, in step S6, the data is decrypted , specifically including the following steps: S61: For the input ciphertext and a set of joint keys , returns a set of bits ,get Minimum; S62: Convert the binary number into a decimal number and output the final result; S63: Verify the correctness of the result and calculate the error rate and the average time of the entire addition operation.

[0018] Therefore, the present invention adopts the above-mentioned multi-key data aggregation method for Internet of Vehicles, which has the following beneficial effects: (1) The present invention adopts a fully homomorphic encryption technology on a multi-key ring to ensure that data is in ciphertext form during transmission and aggregation, and encryption operations are performed on the ring, thereby improving computing efficiency and decryption accuracy.

[0019] (2) The present invention can protect the data information of each vehicle in the Internet of Vehicles, prevent unauthorized institutions or attackers from obtaining it, and ensure the security and correctness of the aggregation process. Even if the gateway or a third party has part of the key, it cannot crack or obtain the plaintext data.

[0020] (3) In the entire data processing process, the present invention further improves data confidentiality and processing efficiency through multi-layer encryption and homomorphic operations, providing effective technical support for the information security of the Internet of Vehicles.

[0021] (4) The present invention not only enhances data security, but also improves processing efficiency, and is suitable for Internet of Vehicles application scenarios that have high requirements for data privacy and security.

[0022] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A system model diagram of a multi-key data aggregation method for networked vehicles according to the present invention; Figure 2 A flowchart of a multi-key data aggregation method for a networked vehicle according to the present invention; Figure 3 It is a key generation diagram of a multi-key data aggregation method for a networked vehicle according to the present invention; Figure 4 It is a schematic diagram of a half adder in a homomorphic operation of a multi-key data aggregation method for a networked vehicle according to the present invention; Figure 5 It is a schematic diagram of a carry device in a homomorphic operation of a multi-key data aggregation method for a networked vehicle according to the present invention; Figure 6 It is a line graph of experimental results of using adders with different bit numbers to run the protocol disclosed in the present invention in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0025] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0026] The words "include" or "comprises" and the like used in the present invention mean that the elements before the word include the elements listed after the word, and do not exclude the possibility of also including other elements. The orientation or position relationship indicated by the terms "inside", "outside", "upper", "lower", etc. is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation of the present invention. When the absolute position of the described object changes, the relative position relationship may also change accordingly. In the present invention, unless otherwise clearly specified and limited, the terms "attachment" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral body; it can be directly connected, or indirectly connected through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0027] like Figure 1-Figure 6 As shown, a multi-key data aggregation method for the Internet of Vehicles specifically includes the following steps: Step S1: the string system generates and initializes the public parameters of LWE and RLWE, including the dimensions, key distribution and error parameters for LWE instance generation and encryption scheme, and the key distribution and error parameters of the public reference string model based on RLWE; In step S1, generate system parameters Set the fixed parameters as input and call and Two algorithms generate LWE parameters respectively and RLWE parameters , output common parameters ; Specifically include the following steps: S11: Generate a security parameter , The algorithm will be safe parameters As input, it generates the dimensions used in LWE instance generation and encryption schemes , Key Distribution and error parameters ; S12: Vector for gadgets Set the decomposition base and degree ; S13: Initialize and output a LWE common parameter , where the key used in the LWE encryption scheme is From the distribution The gadget vector used when randomly sampling and key transformation in the subsequent aggregation process About The basis decomposition algorithm is to convert the elements Convert to Dimensional vector , the coefficient is and make Minimize, default As part of the input; Generate Parameters The specific steps include: S1-1: Setting the required dimensions in the RLWE encryption scheme , yes The power of S1-2: Setting key distribution exist , and select the error parameter ; S1-3: Set base integer And the decomposition degree is Gadgets Vector ; S1-4: Generate a random vector ; S1-5: Output a RLWE common parameter ,RLWE’s encryption scheme is based on the public reference string CRS model, is part of the input.

[0028] Step S2: randomly generate the private key of the participant according to the public parameters generated by the string system, and generate the corresponding public key, bootstrap key and key conversion key based on the private key; In step S2, generate private key and public key , specifically including the following steps: S21: Call Algorithm generation The private key required by each party ; is based on a given LWE key and , open to the entire system from arrive Key conversion key , in Among the participants, for each , No. The items involved and By random sampling and Generate and return ;in ; S22: Call , and These three algorithms generate public keys , Bootstrap Key and key conversion key , returns the user's private key , discloses to all parties and entities a key consisting of a public key, a bootstrap key, and a key conversion key The triple of ; It means from Randomly sample keys ,set up ,from Randomly sampled noise vector , and set the public key to ,run Algorithm to generate RLWE key , and set the public key of the entire system to ; The private key held by the user is used as a key Perform encryption calculations as follows and return the ciphertext : (a) From Random sampling from and error , the output vector ; (b) From Random sampling and , output ciphertext ; in .

[0029] Step S3: The floating point data collected by the connected vehicle is processed into integers and converted into binary form; In step S3, data processing is performed to input the data collected by the connected vehicle ICV. The data type is floating point data, and four decimal places are retained. The floating point data is converted into a processable integer form, and then the integer is converted into a binary number.

[0030] Step S4: Perform LWE encryption on the processed binary data to generate ciphertext, and send the ciphertext to the gateway; In step S4, the data is encrypted For each bit of input , call Encrypt and return to LWE format ,After performing this operation, ICV sends the ciphertext together with the index of the relevant ,participants to the gateway GW; The processed The first participant bit binary data As input, randomly sample and noise , generate ciphertext , which satisfies .

[0031] Step S5: After receiving the ciphertext, the gateway uses homomorphic encryption technology to perform homomorphic operations on the ciphertext, specifically including the gateway performing ciphertext expansion and addition operations on the ciphertexts received from multiple participants; performing isomorphic evaluation operations such as XOR, AND, or OR through a multi-key bootstrap algorithm to generate an aggregated ciphertext and send it to the cloud of CNIC, an Internet of Vehicles information technology company. The cloud uses a key conversion key to convert the aggregated ciphertext into a ciphertext that can ultimately be decrypted with a joint key, and returns the final encryption result; In step S5, the homomorphic operation specifically includes the following steps: S51: performing ciphertext expansion on two ciphertexts at a certain position of two input addends; S52: perform addition operation on the two expanded ciphertexts; in step S52, due to the different number of additions for different bit lengths, the custom bit adder includes various gate circuits, half adders, carry devices, one-bit adders and fast full bootstrap algorithms, and the code is looped multiple times. The algorithm realizes a multi-bit original code adder connected in series with multiple single-bit original code adders. A single-bit original code adder includes a half adder and a carry device. A half adder consists of two XOR gates, and a carry device consists of three AND gates and two OR gates.

[0032] A single-bit original code adder adds the data of two parties. The gate circuit bootstrap algorithm involved will convert the ciphertext generated by the two parties into and , a carry information and key triplet As input, the specific situation is as follows: Multi-key bootstrap AND gate :First, Mapping to Ring Generate a message ,calculate ,Will and , as part of the next homomorphic evaluation phase; Multi-key bootstrap OR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Multi-key bootstrap XOR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Half Adder : Called twice , output a single bit without carry as the result of that bit; Carry : Call three times , output the carry information generated by the two addends; One-bit original code adder : Call and Generate The addition result of the bits is output.

[0033] S53: Use To initialize the homomorphic accumulator, use To calculate recursively; S54: Using the key to convert the key Convert the ciphertext into ciphertext that can ultimately be decrypted using the joint key and output the result.

[0034] In the homomorphic data aggregation operation of step S5, the gateway GW receives the data and performs ciphertext expansion and calculation based on the expanded ciphertext , the calculated Transmitted to the public cloud hired by CNIC; After receiving the data transmitted by GW, the cloud employed by CNIC performs bootstrapping and key conversion homomorphic data aggregation operations. Homomorphic addition data aggregation includes the following steps: Step 1: Ciphertext expansion: GW receives the ciphertexts of the two participants sent by the connected vehicle ICV. and and the key triplet corresponding to the participant sent by the key server (KS) , the ciphertext and Expand into and , the extended ciphertext is the joint key The result of encrypting the same information; Step 2: GW uses two extended ciphertexts and calculate , the calculated Transmitted to the public cloud hired by CNIC; Step 3: Bootstrapping: After receiving the data, the cloud ,calculate and , initialize the RLWE type ciphertext ; in ,make ,run For all and Perform recursive calculation , the bootstrap will output for the next step ; Specifically, This algorithm takes as input a given multi-key ciphertext , a single encrypted ciphertext and a collection of public keys , will calculate and output . Mentioned here There are two different outer product algorithms: Method 1: Using ciphertext generated by single encryption and a set of public keys Generate extended RGSW ciphertext , which is then multiplied using the multi-key outer product , the specific steps are as follows: 1) Ciphertext extension part :for , for all calculate and , generating the vector .Right now ,in is a matrix whose ℓth row vector is . Output an extended ciphertext ; 2) External product part :For multi-key RLWE type ciphertext and a multi-key RGSW-type ciphertext ,calculate And output .

[0035] Method 2: Given a multi-key RLWE ciphertext , first calculate all The following polynomials: ; ; ; ; Then, the multi-key RLWE ciphertext is returned. ,in , , and for In terms of .

[0036] By making a trade-off between storage and complexity, method 1 has an advantage in terms of complexity after preprocessing (about three-quarters). However, method 2 has a smaller noise increase, and smaller parameters can be used to obtain the same noise level in method 1. Therefore, method 2 is more practical and more efficient than method 1.

[0037] Step 4: Key conversion: CNIC employs the cloud to receive ,make for The constant term of is for of The coefficient vector of LWE ciphertext ,make ,run Calculate the final ciphertext , and send the final result to CNIC, where The algorithm will be based on the ciphertext sent by GW in and the conversion key published by KS sequence, for all participants calculate , and let satisfy , returns the ciphertext ,The key conversion algorithm will take the input extended ciphertext and the key conversion key and calculate the ciphertext of the same message under the joint key encryption.

[0038] Will Convert to LWE ciphertext , and calls and runs the multi-key conversion algorithm. As described above, for all , equal Therefore, for , the LWE ciphertext returned in step 4 satisfy Finally, the LWE key corresponding to the ciphertext encryption is converted into a joint key , so that the output LWE ciphertext can satisfy requirements.

[0039] Step S6: Decrypt the aggregated ciphertext using the joint key to obtain the final aggregated result. , specifically including the following steps: S61: For the input ciphertext and a set of joint keys , returns a set of bits ,get Minimum; S62: Convert the binary number into a decimal number and output the final result; S63: Verify the correctness of the result and calculate the error rate and the average time of the entire addition operation.

[0040] Example A multi-key data aggregation method for connected vehicles is applied to the data aggregation process in the Internet of Vehicles scenario, which has significant effects in terms of efficiency and security. There are 4 entities: (1) Internet-connected vehicle (ICV): ICV is equipped with a car computer and has basic computing capabilities. Its function is to collect real-time data and perform simple encryption calculations, and upload the data to the gateway through its own bandwidth line. The key here comes from the KS in the CNIC, which is responsible for distributing a key to each ICV in a region for preliminary data encryption. The functional goal of ICV is that it can encrypt the collected real-time data according to the received private key and transmit the encrypted data to the next participating entity.

[0041] (2) Gateway (GW): The main function is to receive the encrypted data within the area and perform preliminary aggregation operations, that is, Gateway 1 collects data from Area 1, and Gateway 2 collects data from Area 2. After the integration operation is completed, all encrypted data will be initially aggregated. The collected ciphertext will be expanded to obtain the extended ciphertext, and then an addition operation will be performed to obtain a result, and all the initially aggregated data will be transmitted to the computing center.

[0042] (3) Internet of Vehicles Information Technology Company (CNIC): It is a platform that provides traffic information sharing, future traffic situation prediction, and real-time vehicle status information aggregation. Because it does not have a large computing power, it will rent a public cloud to aggregate and calculate ICV data for it. The hired public cloud will provide aggregate computing data services to CNIC, using the data transmitted by the GW and the key triples required for subsequent aggregation operations transmitted by the key server to perform data aggregation operations and transmit the final results to CNIC. After the hired cloud computing generates the aggregation results, the key distributed by the key server is used to decrypt the data. It needs to ensure that the hired cloud can correctly aggregate the data, and the department in CNIC responsible for analyzing the data and counting the Internet of Vehicles information can decrypt the correct results based on the key.

[0043] (4) Key Server (KS): A department in CNIC that provides a place for different entities in the entire system to obtain the required keys. It is a fully trusted system member by default. It needs to have simple computing capabilities to generate parameters and different keys to meet the encryption requirements of the entire scheme. Its functional goal is to correctly distribute keys and ensure the privacy of keys.

[0044] The system takes the fixed parameters set at the beginning as input and calls and Two algorithms, among which, for :The system will first generate a security parameter , the dimension of the generated LWE solution (n is 560), key distribution and error parameters ( Pick ), set the decomposition basis and degree Generate Gadget Vector ( Pick , Take 8), output a LWE common parameter .for : Set the required dimension in the RLWE encryption scheme ( Take 1024) and error parameters , set the base integer And the decomposition degree is Gadgets Vector ( Pick , Take 3), generate a random vector , output RLWE common parameters , and finally output the system common parameters .

[0045] System Operation Algorithm, from Randomly sample keys as the user's private key. Run Algorithm to generate RLWE key , and set the public key of the entire system to .run The private key held by each user will be used with the key Perform encryption calculations and return the bootstrap key .run Algorithm to generate key conversion key .in, Indicates Participants, the value can be 2. Finally, distribute the corresponding user private keys to all participants , disclose to CNIC the public key, bootstrap key and key conversion key triplet of each participant user .

[0046] The input user power consumption (floating point data) is retained in the form of only one decimal place, and then uniformly multiplied by 10 to become a ten-fold integer form, and then converted into a 4 to 12-bit (determined by the data size) binary number through the binary conversion step. Each binary number of each participant's data is returned and displayed in sequence.

[0047] ICV for the input The first participant bit binary data ,run The algorithm takes the processed data as input and randomly samples and noise , generate ciphertext (Which satisfies ). Finally, the ciphertext is sent to the GW along with the index of the relevant participants.

[0048] GW receives the ciphertexts of the two parties sent by ICV. and ( Only indicates the difference between the participants), and KS also sends the key triples corresponding to the participants Send to GW. GW sends the ciphertext and Expand into and , the extended ciphertext is the joint key The result of encrypting the same information. GW is based on two extended ciphertexts and calculate , the last calculated The data is transmitted to the public cloud hired by CNIC. After the cloud receives the data, it ,calculate and Initialize RLWE ciphertext ,in .make ,run For all and Perform recursive calculation The public cloud hired by CNIC received ,make for The constant term of is for of The coefficient vector of LWE ciphertext .make ,run Calculate the final ciphertext , and send the final result to CNIC. The algorithm will be based on the ciphertext sent by GW in and the conversion key published by KS sequence, for all participants calculate , and let satisfy . Return ciphertext .

[0049] The relevant analysis and statistics department of CNIC received the final aggregated results of the public cloud computing companies hired. After that, all participants will use the joint key distributed by KS , calculate bits , so that Minimum.

[0050] This embodiment is run on a computer with an Intel i7-10510U with a main frequency of 1.80GHz / 2.30GHz. VMware Workstation 17.5 is installed and Linux system CentOS 7 is configured, and 4GB of memory, 4 processors, and 48GB of hard disk space are allocated to it. All algorithms are written in C++ language, using MK-TFHE library and TFHE library.

[0051] In homomorphic operations, the accumulation step after constructing the accumulator is the most expensive part of the entire pipeline, while all other algorithms including multi-key transformations are asymptotically faster. Figure 6 As shown in Figure 1, we found that when running this protocol, the greater the total number of operations, the greater the total running time overhead when using adders of different bit sizes. However, it does not show a linear growth trend, but the slope decreases as the total number of operations increases.

[0052] When the adversary tries to steal the key, the key generated by the key conversion algorithm and the key generated by the RLWE related algorithm are The difficult assumptions and parameters of the LWE problem are The RLWE problem of is assumed to be unbreakable, so the adversary cannot steal the key.

[0053] When the adversary attempts to launch a third-party forgery attack, the adversary cannot successfully launch a third-party forgery attack because the privacy protection of this method is based on the security of the multi-key scheme and the adversary cannot crack the encryption scheme of this paper within polynomial time.

[0054] When an adversary tries to obtain data information from encrypted data, the adversary cannot obtain data information from encrypted data because the data is generated by ciphertext encrypted by all participants with their own private keys, after expansion processing, and then obtained through homomorphic calculation by a specific gate circuit. At the same time, no participant or entity has all the keys involved in the entire data aggregation scheme, and the calculations given by each GW in the homomorphic calculation process are executed independently.

[0055] When the adversary tries to forge the data in this method and pass the decryption authentication, since KS distributes the key triple required for the public cloud computing hired by CNIC All of them were distributed to participants in advance. Private key Therefore, the adversary cannot forge the ciphertext to perform homomorphic operations, let alone pass decryption authentication.

[0056] Therefore, the present invention adopts the above-mentioned multi-key data aggregation method for the Internet of Vehicles. In the entire data processing process, through multi-layer encryption and homomorphic operations, the confidentiality and processing efficiency of the data are further improved, and effective technical support is provided for the information security of the Internet of Vehicles. It not only enhances the security of the data, but also improves the processing efficiency. It is suitable for Internet of Vehicles application scenarios with high requirements for data privacy and security.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A multi-key data aggregation method for Internet of Vehicles, characterized by: The specific steps include: Step S1: The string system generates and initializes the public parameters of LWE and RLWE, including the dimensions, key distribution and error parameters for LWE instance generation and encryption scheme, and the key distribution and error parameters of the public reference string model based on RLWE; Step S2: Randomly generate the private key of the participant according to the public parameters generated by the string system, and generate the corresponding public key, bootstrap key and key conversion key based on the private key; Step S3: The floating point data collected by the connected vehicle is processed into integers and converted into binary form; Step S4: Perform LWE encryption on the processed binary data to generate ciphertext, and send the ciphertext to the gateway; Step S5: After receiving the ciphertext, the gateway uses homomorphic encryption technology to perform homomorphic operations on the ciphertext, specifically including the gateway performing ciphertext expansion and addition operations on the ciphertexts received from multiple participants; performing isomorphic evaluation operations such as XOR, AND, or OR through a multi-key bootstrap algorithm to generate an aggregated ciphertext and send it to the cloud of CNIC, an Internet of Vehicles information technology company. The cloud uses a key conversion key to convert the aggregated ciphertext into a ciphertext that can ultimately be decrypted with a joint key, and returns the final encryption result; Step S6: Decrypt the aggregated ciphertext using the joint key to obtain the final aggregation result.

2. A multi-key data aggregation method for Internet of Vehicles according to claim 1, characterized in that: In step S1, generate system parameters Set the fixed parameters as input and call and Two algorithms generate LWE parameters respectively and RLWE parameters , output common parameters ; The specific steps include: S11: Generate a security parameter , The algorithm will be safe parameters As input, it generates the dimensions used in LWE instance generation and encryption schemes , Key Distribution and error parameters ; S12: Vector for gadgets Set the decomposition base and degree ; S13: Initialize and output a LWE common parameter , where the key used in the LWE encryption scheme is From the distribution The gadget vector used when randomly sampling and key transformation in the subsequent aggregation process About The basis decomposition algorithm is to convert the elements Convert to Dimensional vector , the coefficient is and make Minimize, default As part of the input; Generate Parameters The specific steps include: S1-1: Setting the required dimensions in the RLWE encryption scheme , yes The power of S1-2: Setting key distribution exist , and select the error parameter ; S1-3: Set base integer And the decomposition degree is Gadgets Vector ; S1-4: Generate a random vector ; S1-5: Output a RLWE common parameter ,RLWE’s encryption scheme is based on the public reference string CRS model, is part of the input.

3. A multi-key data aggregation method for Internet of Vehicles according to claim 2, characterized in that: In step S2, generate private key and public key , specifically including the following steps: S21: Call Algorithm generation The private key required by each party ; is based on a given LWE key and , open to the entire system from arrive Key conversion key , in Among the participants, for each , No. The items involved and By random sampling and Generate and return ;in ; S22: Call , and These three algorithms generate public keys , Bootstrap Key and key conversion key , returns the user's private key , discloses to all parties and entities a key consisting of a public key, a bootstrap key, and a key conversion key The triple of ; It means from Randomly sample keys ,set up ,from Randomly sampled noise vector , and set the public key to ,run Algorithm to generate RLWE key , and set the public key of the entire system to ; The private key held by the user is used as a key Perform encryption calculations as follows and return the ciphertext : (a) From Random sampling from and error , the output vector ; (b) From Random sampling and , output ciphertext ; in .

4. A multi-key data aggregation method for Internet of Vehicles according to claim 3, characterized in that: In step S3, data processing is performed to input the data collected by the connected vehicle ICV. The data type is floating point data, and four decimal places are retained. The floating point data is converted into a processable integer form, and then the integer is converted into a binary number.

5. A multi-key data aggregation method for Internet of Vehicles according to claim 4, characterized in that: In step S4, the data is encrypted For each bit of input , call Encrypt and return to LWE format ,After performing this operation, ICV sends the ciphertext together with the index of the relevant ,participants to the gateway GW; The processed The first participant bit binary data As input, randomly sample and noise , generate ciphertext , which satisfies .

6. A multi-key data aggregation method for Internet of Vehicles according to claim 5, characterized in that: In step S5, the homomorphic operation specifically includes the following steps: S51: performing ciphertext expansion on two ciphertexts at a certain position of two input addends; S52: performing an addition operation on the two expanded ciphertexts; S53: Use To initialize the homomorphic accumulator, use To calculate recursively; S54: Using the key to convert the key Convert the ciphertext into ciphertext that can ultimately be decrypted using the joint key and output the result.

7. A multi-key data aggregation method for Internet of Vehicles according to claim 6, characterized in that: In step S52, due to the different number of additions for different bit lengths, the custom bit adder includes various gate circuits, half adders, carry devices, one-bit adders and fast full bootstrap algorithms, and the code is looped multiple times. The algorithm realizes a multi-bit original code adder connected in series with multiple single-bit original code adders. A single-bit original code adder includes a half adder and a carry device. A half adder consists of two XOR gates, and a carry device consists of three AND gates and two OR gates.

8. A multi-key data aggregation method for Internet of Vehicles according to claim 7, characterized in that: A single-bit original code adder adds the data of two parties. The gate circuit bootstrap algorithm involved will convert the ciphertext generated by the two parties into and , a carry information and key triplet As input, the specific situation is as follows: Multi-key bootstrap AND gate :First, Mapping to Ring Generate a message ,calculate ,Will and , as part of the next homomorphic evaluation phase; Multi-key bootstrap OR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Multi-key bootstrap XOR gate :First, Mapping to Ring Generate a message ,calculate ,Will and as input as part of the next homomorphic evaluation phase; Half Adder : Called twice , output a single bit without carry as the result of that bit; Carry : Call three times , output the carry information generated by the two addends; One-bit original code adder : Call and Generate The addition result of the bits is output.

9. A multi-key data aggregation method for Internet of Vehicles according to claim 8, characterized in that: In the homomorphic data aggregation operation of step S5, the gateway GW receives the data and performs ciphertext expansion and calculation based on the expanded ciphertext , the calculated Transmitted to the public cloud hired by CNIC; After receiving the data transmitted by GW, the cloud employed by CNIC performs bootstrapping and key conversion homomorphic data aggregation operations. Homomorphic addition data aggregation includes the following steps: Step 1: Ciphertext expansion: GW receives the ciphertexts of the two participants sent by the connected vehicle ICV. and and the key triplet corresponding to the participant sent by the key server (KS) , the ciphertext and Expand into and , the extended ciphertext is the joint key The result of encrypting the same information; Step 2: GW uses two extended ciphertexts and calculate , the calculated Transmitted to the public cloud hired by CNIC; Step 3: Bootstrapping: After receiving the data, the cloud ,calculate and , initialize the RLWE type ciphertext ; in ,make ,run For all and Perform recursive calculation , the bootstrap will output for the next step ; Step 4: Key conversion: CNIC employs the cloud to receive ,make for The constant term of is for of The coefficient vector of LWE ciphertext ,make ,run Calculate the final ciphertext , and send the final result to CNIC, where The algorithm will be based on the ciphertext sent by GW in and the conversion key published by KS sequence, for all participants calculate , and let satisfy , returns the ciphertext ,The key conversion algorithm will take the input extended ciphertext and the key conversion key and calculate the ciphertext of the same message under the joint key encryption.

10. A multi-key data aggregation method for Internet of Vehicles according to claim 9, characterized in that: In step S6, the data is decrypted , specifically including the following steps: S61: For the input ciphertext and a set of joint keys , returns a set of bits ,get Minimum; S62: Convert the binary number into a decimal number and output the final result; S63: Verify the correctness of the result and calculate the error rate and the average time of the entire addition operation.

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