Privacy preserving data aggregation method for safety enhancement in intelligent transportation systems

Abstract

The application discloses a privacy protection data aggregation method for security enhancement in an intelligent transportation system, which realizes vehicle position privacy and data privacy protection by adopting the Chinese remainder theorem, a Paillier encryption system and T-N threshold secret sharing technology, and simultaneously obtains statistical results of mean and variance; in addition, the threshold secret sharing improves the security of a server, and ensures that an attacker cannot obtain aggregation data of the server in the case of compromising less than a threshold number of servers; finally, identity signature technology with batch verification is adopted to realize data integrity and identity authentication in a communication process. On the basis of realizing data aggregation, protecting vehicle position privacy and data privacy, the method obtains more data analysis results, and improves the ability of the server to resist single-point attacks.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation systems, and more specifically, to a method for enhancing security and protecting privacy in intelligent transportation systems through data aggregation. Background Technology

[0002] With the rapid development and widespread deployment of the Internet of Vehicles (IoV), Intelligent Transportation Systems (ITS) are playing a crucial role across various industries as a typical application. As an important branch of the Internet of Things (IoT) and an extension of Vehicle Ad Hoc Networks (VANETs), IoV primarily focuses on information interaction between vehicles, roadside units, and the environment without human intervention. Simultaneously, with the rapid advancement of science and technology, vehicle sensor devices (including temperature sensors, crankshaft position sensors, and vehicle speed sensors) are able to collect and record more accurate data. ITS can then comprehensively monitor vehicles and driving areas based on the sensor data, and provide accurate and practical data services to vehicle users based on the analyzed and acquired data. Widely used intelligent transportation services include autonomous driving, road hazard warnings, real-time fuel and electricity consumption monitoring, and intelligent navigation.

[0003] Secure and privacy-preserving data aggregation schemes have garnered significant attention from scholars in the field since the emergence of the Internet of Things (IoT). With the extensive and in-depth research on intelligent transportation systems, several secure and privacy-preserving data aggregation schemes have been proposed, but all of them harbor some security risks. For example, data aggregation often leads to issues such as user information leakage and low utilization of perceived data. These problems severely impact users' enthusiasm for participating in traffic data collection and are detrimental to the long-term development of intelligent transportation systems. Summary of the Invention

[0004] The purpose of this invention is to provide a privacy-preserving data aggregation method for enhanced security in intelligent transportation systems. This method can prevent attackers from using data reports to infer users' driving routes and other privacy information, improve the server's ability to resist single-point attacks, and obtain more data analysis results, thereby enhancing the accuracy and usability of the analysis results.

[0005] To achieve the above objectives, the present invention provides a security-enhanced privacy-preserving data aggregation method for intelligent transportation systems, the method comprising:

[0006] Step 1: The Key Management Center initializes the data and sets a region number ξ for each region. i and the private key Send to the vehicle, with the private key Send the private key to the roadside unit. Send to the traffic management center; set a shared key s1 between the vehicle and the roadside unit, and send the shared key f(i) calculated by the (T-1)th order polynomial to each server of the traffic management center; after the key is distributed to the specific entity, the key management center is offline;

[0007] Step 2: The traffic management center continuously collects sensing data according to the data collection cycle. The vehicle will then process the sensing data generated by the sensors, d = (d... i，1 d i，2 , ...,d i，l ), e = (e i，1 e i，2 , ..., e i，l Compress and encrypt to C i =C i，1 ||C i，2 ||C i，3 Then a digital signature E is generated. i Y i Package the ciphertext and digital signature into a data report. And upload it to the roadside unit;

[0008] Step 3: The roadside unit receives V i After sending the data report, through the formula Perform identity verification. If the verification is successful, proceed to the next step; otherwise, discard the results.

[0009] Step 4: Use V i The shared key s1 between the traffic management center and the roadside unit is used to decrypt the encrypted sensing data for the first time, obtaining ciphertext C′ that can be decrypted independently by the traffic management center. i，1 C′ i，2 C′ i，3 After the first step of decryption is completed, all ciphertexts are aggregated to form aggregated ciphertext C = C1||C2||C3; digital signature is then applied to the aggregated ciphertext. Package the aggregated ciphertext and digital signature into a data report (ID). RSU After ||C||TS||E||Y), send it to the traffic management center;

[0010] Step 5: After receiving the data report from the roadside unit, the traffic management center first uses the formula... Authentication is performed. If authentication is successful, the T-stage server is selected for the second step of decryption; if authentication fails, the process is discarded.

[0011] Step 6: Select a subset of T-stage servers Each subserver i calculates and corresponding encrypted fragments The calculation results of each sub-server The data is sent uniformly to one of the servers for aggregation, and the server obtains the aggregated plaintext through aggregation. The mean and variance of the perceived data were obtained through calculation.

[0012] Preferably, double encryption is used in Step 2, namely, a shared key s1 is deployed between the vehicle and the roadside unit to ensure that the traffic management center cannot obtain the vehicle's location privacy by capturing the vehicle's data reports.

[0013] Preferably, in Step 6, if an external attacker breaches fewer than the threshold T servers, when the roadside unit uploads the data report to the traffic management center, and the attacker decrypts the aggregated ciphertext through the breached servers, since each individual server contains only one shared key f(i), it cannot complete the decryption of the entire aggregated ciphertext, and thus cannot obtain the perception data of each area.

[0014] Preferably, variance calculation is used in data reading and analysis to display the volatility of the perceived data.

[0015] According to the above technical solution, this invention employs Paillier encryption and a TN threshold secret sharing mechanism to protect vehicle location and data privacy. Simultaneously, it obtains statistical results of mean and variance, enhancing the usability and accuracy of traffic management center decisions and improving service quality. Furthermore, the TN threshold secret sharing mechanism improves server security; if the number of compromised servers is less than the threshold, the attacker cannot obtain the analysis results of the perceived data, effectively resisting single-point attacks. In addition, this method uses batch-verified identity signature technology to achieve data integrity and identity authentication during communication, preventing attackers from impersonating legitimate users to send false data reports or tampering with correct data reports during data report transmission.

[0016] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of the privacy-protected data aggregation method for enhanced security in intelligent transportation systems provided by the present invention;

[0019] Figure 2This is a flowchart illustrating the data report transmission method and key distribution in the security-enhanced privacy-protected data aggregation method for intelligent transportation systems provided by this invention;

[0020] Figure 3 This is a comparison chart of the computational overhead of solutions SEPDA, PSSIV, EPPA, and TES during the data generation phase.

[0021] Figure 4 This is a comparison chart of the computational overhead of solutions SEPDA, PSSIV, and EPPA in the data reading and analysis phases.

[0022] Figure 5 This is a comparison chart of the communication overhead generated by solutions SEPDA and PSSIV when the vehicle uploads data reports to the RSU;

[0023] Figure 6 This is a comparison chart of the communication overhead generated by solutions SEPDA and PSSIV when uploading data reports from RSU to TMC. Detailed Implementation

[0024] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0025] See Figures 1-6 This invention provides a security-enhanced privacy-preserving data aggregation method for intelligent transportation systems, the method comprising:

[0026] Step 1: The Key Management Center initializes the data and sets a region number ξ for each region. i and the private key Send to the vehicle, with the private key Send the private key to the roadside unit. Send to the traffic management center; set a shared key s1 between the vehicle and the roadside unit, and send the shared key f(i) calculated by the (T-1)th order polynomial to each server of the traffic management center; after the key is distributed to the specific entity, the key management center is offline;

[0027] Step 2: The traffic management center continuously collects sensing data according to the data collection cycle. The vehicle will then process the sensing data generated by the sensors, d = (d... i，1 d i，2 , ...,d i，l ), e = (e i，1 e i，2 , ..., e i，l Compress and encrypt to C i =C i，1 ||Ci，2 ||C i，3 Then a digital signature E is generated. i Y i Package the ciphertext and digital signature into a data report. And upload it to the roadside unit;

[0028] Step 3: The roadside unit receives V i After sending the data report, through the formula Perform identity verification. If the verification is successful, proceed to the next step; otherwise, discard the results.

[0029] Step 4: Use V i The shared key s1 between the traffic management center and the roadside unit is used to decrypt the encrypted sensing data for the first time, obtaining ciphertext C′ that can be decrypted independently by the traffic management center. i，1 C′ i，2 C′ i，3 After the first step of decryption is completed, all ciphertexts are aggregated to form aggregated ciphertext C = C1||C2||C3; digital signature is then applied to the aggregated ciphertext. Package the aggregated ciphertext and digital signature into a data report (ID). RSU After ||C||TS||E||Y), send it to the traffic management center;

[0030] Step 5: After receiving the data report from the roadside unit, the traffic management center first uses the formula... Authentication is performed. If authentication is successful, the T-stage server is selected for the second step of decryption; if authentication fails, the process is discarded.

[0031] Step 6: Select a subset of T-stage servers Each subserver i calculates The calculation results of each sub-server mod n 2 The data is sent uniformly to one of the servers for aggregation, and the server obtains the aggregated plaintext through aggregation. The mean and variance of the perceived data were obtained through calculation.

[0032] To defend against various external and internal attacks, the method employs dual encryption in Step 2, namely, deploying a shared key s1 between the vehicle and the roadside unit to ensure that the traffic management center cannot obtain the vehicle's location privacy by capturing the vehicle's data reports.

[0033] In Step 6, if the number of servers compromised by an external attacker is less than the threshold T, when the roadside unit uploads the data report to the traffic management center, the attacker cannot complete the decryption of the aggregated ciphertext by decrypting the aggregated ciphertext through the compromised servers because each individual server only contains one shared key f(i). As a result, the attacker cannot obtain the perception data of each area, thus protecting the user's location privacy.

[0034] Because vehicles are in dynamic motion, the perception data they generate is highly volatile, and a single mean is easily affected by peaks and troughs in the perception data. In data reading and analysis, this method introduces variance calculation, which can better display the volatility of perception data and determine its usability to help intelligent transportation systems make more accurate decisions.

[0035] The following is a specific embodiment to illustrate the present invention:

[0036] 1. Scheme initialization:

[0037] The Key Management Center (KMC) acts as a trusted third party, given a security parameter κ, and uses a generator... generate And select two cryptographic hash functions H and H1, where Meanwhile, select a safety parameter κ1 and two large safety primes p = 2p′ + 1 and q = 2q′ + 1, and set |p| = |q| = |κ1|. Assume... It is modulo n 2 The quadratic residual cyclic group, whose order is The public key of the encryption scheme is pk = (n = pq, g, h = g) z ), private key is

[0038] During the user registration phase, KMC calculates each user's individual private key. It is distributed to vehicles, roadside units, and traffic management centers, and a separate shared key s1 is established between vehicles and roadside units.

[0039] Considering there are l sub-regions, the scheme selects l+1 prime numbers: μ, ξ1, ξ2, ..., ξ l , where |ξ j |=l1,1<j<l。Distribute a separate ξ for each subregion. j Then the traffic management center calculates:

[0040]

[0041] Private key As the secret sharing value, TMC calculates the secret fragment f(i) of server i using formula (2) and distributes the secret fragment to the corresponding server:

[0042]

[0043] Finally, KMC released the system parameters.

[0044] 2. Data report generation:

[0045] The vehicle uploads a data report every 15 minutes. The specific steps for generating the data report are as follows:

[0046] 2.1: According to the Chinese Remainder Theorem, the multidimensional data d = (d i，1 d i，2 , ...d i，l ) and e=(e i，1 e i，2 , ...e i，l Compressed into one-dimensional data

[0047] 2.2: Using random numbers And shared key s1 encryption S i，d S i，e And generate ciphertext:

[0048]

[0049] TS is a timestamp; and C is calculated. i =C i，1 ||C i，2 ||C i，3 .

[0050] 2.3: Select a random number And calculate signature data and

[0051] 2.4: Finally, the vehicle sends a data report. Give it to the roadside unit.

[0052] 3. Data report aggregation:

[0053] The steps for verifying roadside unit data reports and aggregating encrypted sensing data are as follows:

[0054] 3.1: Use the private key to perform bilinear pairing verification on the received data report:

[0055]

[0056] 3.2: Perform the first step of decryption, using the shared key s1 to decrypt the received ciphertext:

[0057]

[0058] The decrypted ciphertext is then processed to obtain the aggregated ciphertext results for all vehicles:

[0059]

[0060] And calculate C = C1||C2||C3.

[0061] 3.3: Select a random number And calculate signature data

[0062] 3.4: Finally, the roadside unit sends a data report (ID). RSU ||C||TS||E||Y) to the traffic management center.

[0063] 4. Data reading and analysis:

[0064] Upon receiving the data report uploaded by the roadside unit, the traffic management center first verifies the identity of the data to ensure its authenticity and integrity. Then, it performs the following steps to read and analyze the data report:

[0065] 4.1: Select T servers in the traffic management center (forming a subset) Decryption calculations are performed by server i based on the server set T. And utilize secret partitioning f(i) and B i calculate

[0066]

[0067] 4.2: Randomly select one server to aggregate the ciphertext calculated by other (T-1) servers, and obtain the plaintext for each region based on the obtained T ciphertexts:

[0068]

[0069] 4.3: Using the acquired plaintext, calculate the mean and variance for each region:

[0070]

[0071]

[0072] After obtaining the average value and variance of the perception data for each road segment, we can better reflect the road traffic conditions, help the intelligent transportation system make better decisions, and improve the safety of users' travel.

[0073] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0074] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0075] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for enhancing security and protecting privacy through data aggregation in an intelligent transportation system, characterized in that, The method includes: Step 1: The Key Management Center initializes the data and sets a region number ξ for each region. i and the private key Send to the vehicle, with the private key Send the private key to the roadside unit. Send to the traffic management center; set a shared key s1 between the vehicle and the roadside unit, and send the shared key f(i) calculated by the (T-1)th order polynomial to each server of the traffic management center; after the key is distributed to the specific entity, the key management center is offline; Step 2: The traffic management center continuously collects sensing data according to the data collection cycle. The vehicle will then process the sensing data generated by the sensors, d = (d... i，1 d i，2 , ...,d i，l ), e = (e i，1 e i，2 , ..., e i，l Compress and encrypt to C i =C i，1 ||C i，2 ||C i，3 Then a digital signature E is generated. i Y i Package the ciphertext and digital signature into a data report. And upload it to the roadside unit; Step 3: The roadside unit receives vehicle V i After sending the data report, through the formula Perform authentication, where P is Generator, TS is the timestamp of the current time, P Pub For public keys issued by the key management center, It is a bilinear pairing function, and H1() is a hash function; if authentication is successful, proceed to the next step; if authentication fails, discard. Step 4: Use V i The shared key s1 between the traffic management center and the roadside unit is used to decrypt the encrypted sensing data for the first time, obtaining ciphertext C′ that can be decrypted independently by the traffic management center. i，1 C′ i，2 C′ i，3 After the first step of decryption is completed, all ciphertexts are aggregated to form aggregated ciphertext C = C1||C2||C3; then a random number is selected. Digital signature on aggregated ciphertext in The private key for RSU; package the aggregated ciphertext and digital signature into a data report (ID). RSU After ||C||TS||E||Y), send it to the traffic management center; Step 5: After receiving the data report from the roadside unit, the traffic management center first uses the formula... Authentication is performed. If authentication is successful, the T-stage server is selected for the second step of decryption; if authentication fails, the process is discarded. Step 6: Select a subset of T-stage servers Each subserver i calculates and corresponding encrypted fragments Where f(i) is the secret shard of each server; the computation result of each sub-server The data is uniformly sent to one of the servers for aggregation, and this server obtains the aggregated value of the perceived data. Aggregate value of vehicle count in each region The mean and variance of the perceived data were obtained through calculation.

2. The privacy-preserving data aggregation method for enhanced security in intelligent transportation systems according to claim 1, characterized in that, Step 2 employs dual encryption, which involves deploying a shared key s1 between the vehicle and the roadside unit to ensure that the traffic management center cannot obtain the vehicle's location privacy by capturing the vehicle's data reports.

3. The privacy-preserving data aggregation method for enhanced security in intelligent transportation systems according to claim 1, characterized in that, In Step 6, if an external attacker breaches fewer than the threshold T servers, when the roadside unit uploads the data report to the traffic management center, the attacker cannot complete the decryption of the aggregated ciphertext by decrypting the aggregated ciphertext through the breached servers because each individual server only contains one shared key f(i), thus failing to obtain the perception data of each area.

4. The privacy-preserving data aggregation method for enhanced security in intelligent transportation systems according to claim 1, characterized in that, Variance calculations are used in data reading and analysis to reveal the volatility of perceived data.

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