Multi-level user anonymous security authentication method and system based on game theory trust evaluation mechanism

Abstract

The application discloses a multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, constructs a Nash equilibrium model of a user and a system based on a game theory, designs a probability for strategy selection in authentication strength based on a user trust level by an edge server, solves a static rule problem in dynamic risk assessment, allows the edge server and the user to form a dynamic game cycle, simultaneously solves a limitation of one-way assessment, realizes a cooperative evolution of a defense strategy and user behavior, introduces an incentive mechanism when designing a trust score function, guides the user to actively maintain a high trust state, and supplements a one-way punishment mechanism of dynamic risk assessment. In order to protect data privacy, trust score calculation is divided into steps, data preprocessing and local calculation are carried out on the edge server, local calculation results of different authentication factor behavior data are sent to a TA by using homomorphic encryption and a public key signature, and the local calculation results are aggregated and calculated, and the trust score is updated according to a historical trust score of the user.

Description

Technical Field

[0001] This application relates to the field of autonomous driving information security technology, specifically to a multi-level user anonymity security authentication method and system based on a game theory trust evaluation mechanism. Background Technology

[0002] Currently, most identity authentication processes employ dynamic risk assessment methods to classify users, using machine learning algorithms to analyze user behavior and environmental context in real time and automatically adjust authentication levels. However, this method overlooks user behavioral strategies; for example, users may intentionally evade authentication. Furthermore, existing methods only address risk through penalties, lacking positive incentives for honest behavior. In addition, current dynamic risk assessment methods unilaterally assign risk scores to users without considering the game between users and the system. The system cannot guide user behavior by dynamically adjusting authentication strategies, resulting in a passive defense mechanism.

[0003] Many algorithms for calculating dynamic trust scores are executed on edge computing nodes or central nodes. Techniques that execute on edge computing nodes do not consider that edge computing nodes are honest and curious (i.e., they strictly follow the set program steps, but attackers may be able to compromise them and obtain data). Storing the calculated data on edge computing nodes may lead to malicious attackers modifying users' trust scores. On the other hand, techniques that execute on central nodes store a large number of computational tasks on the central node. Although this ensures data security, it does not consider the computational time complexity, which will place a heavy computational burden on the central node.

[0004] Therefore, there is an urgent need for a user security authentication method that can achieve a dynamic balance between security and user experience. Summary of the Invention

[0005] Purpose of the Invention: To overcome the above shortcomings, the purpose of this application is to provide a multi-level anonymous user security authentication method and system based on a game theory trust evaluation mechanism. By modeling the interaction behavior between users and edge authentication servers, a dynamic balance between security and user experience is achieved. Homomorphic encryption is adopted, and the edge server performs data preprocessing and local calculation on user behavior data for different authentication factors. Each data is homomorphically encrypted, and the encryption result is digitally signed using the edge server's private key and transmitted to the TA. The TA performs aggregate calculation without decrypting individual data, and updates the trust score based on game theory according to the user's historical trust score, thus ensuring the privacy protection and data security of the user's trust score.

[0006] To address the aforementioned technical problems, this application provides a multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism, comprising:

[0007] S1: Based on the ride-hailing request from the registered user terminal, generate matching user information and encrypt the user information using the public key of the registered edge computing server to generate user ciphertext;

[0008] S2: Decrypt the user's ciphertext using the edge server key to obtain user information;

[0009] S3: Complete two-factor authentication and negotiate a session key by verifying the validity of the timestamp, and then store the session key in the cloud storage server and use it as the session key for the user terminal's subsequent ride-hailing application;

[0010] S4: Dispatch the nearest available registered intelligent and autonomous vehicle around the passenger terminal and encrypt the session key and user information using the public key of the intelligent and autonomous vehicle;

[0011] S5: Uses session keys to perform mutual authentication between the user terminal and intelligent and autonomous vehicles, and updates the user trust score and session key after authentication so that the session key can be used for subsequent communication.

[0012] As a preferred embodiment of this application, when a user terminal registers with the registration center, the method includes:

[0013] S101: When the Trusted Authority Center (TA) checks that the user terminal's identity does not exist through facial biometrics and phone number verification, it generates a user identity for the user terminal based on the user terminal's phone number. And random number As the user's private key;

[0014] S102: Select large prime numbers P1 and P2 and the elliptic curve base point G, and calculate the user terminal public key. in, The ECC is modulo a large prime number P1;

[0015] S103: Issue digital certificates to newly registered user terminals Where H represents hash calculation, ⊕ represents XOR operation, and its trust score is initialized to b; then... The registration result is returned to the user terminal via a secure channel, and the TA stores relevant information about the user terminal. This is public information.

[0016] As a preferred embodiment of this application, when an edge computing server registers with a registry center, the method includes:

[0017] S111: Trusted Authority Center (TA) generates identity codes for edge computing servers. And random number As the private key for the edge computing server;

[0018] S112: Compute the public key for the edge computing server

[0019] S113: Chebyshev chaotic mapping code for computing edge servers in, Representative with For order, The Chebyshev chaotic mapping value of the parameter. This means identifying the edge server. Use hash calculation and naturally connect it to the public key; S114: Store relevant information for the edge server and... Send to the edge computing server via a secure channel. This is public information.

[0020] As a preferred embodiment of this application, when intelligent and autonomous vehicles register with a registry center, the method includes:

[0021] S115: Trusted Authority Center (TA) generates identification codes for intelligent and autonomous vehicles. And random number As a private key for intelligent and autonomous vehicles;

[0022] S116: Allocate matching edge computing servers based on the operating service area of ​​intelligent and autonomous vehicles;

[0023] S117: Computational Intelligence and Public Keys for Autonomous Vehicles

[0024] S118: Stores information related to intelligent and autonomous vehicles and will Send to intelligent and autonomous vehicles via a secure channel. This is public information.

[0025] As a preferred embodiment of this application, in step S1, the method includes:

[0026] S121: Generate the current timestamp TS1 based on the first ride-hailing request sent by the registered user terminal to the edge computing server;

[0027] S122: Use the digital certificate and timestamp TS1 with the edge computing server's public key. Encryption is performed to obtain the user's ciphertext. The message verification code MACU-E is calculated using the SHA256 hash: H(TS1||E) U-E ), where ENC is the encryption method.

[0028] S123: Transfer timestamp TS1 and ciphertext E U-E With message verification code MACU-E Send to the edge computing service node.

[0029] As a preferred embodiment of this application, in step S2, the method includes:

[0030] S201: Based on the public key calculation formula used by the edge server during the registration phase, decrypt the user's ciphertext using the edge server's key to obtain... DEC stands for decryption;

[0031] S202: Based on the probability in the hybrid game model, choose to implement either a strict authentication strategy or a basic authentication strategy. If the strict authentication strategy is adopted, a data request is sent to the TA based on the obtained user digital certificate. The user information stored in the TA is obtained through a secure channel. The user's historical authentication records and trust level are compared, and the authentication factors are strictly verified to ensure that they are correct and without omissions according to the trust level. If the basic authentication strategy is adopted, only the basic legality of the authentication factors is verified, and no historical behavior correlation analysis is performed.

[0032] As a preferred embodiment of this application, in step S3, the method further includes:

[0033] S301: After obtaining user information, determine the validity of the timestamp. First-factor verification was performed; among them, T cur1 The current time is ΔT, and the effective time interval is ΔT.

[0034] S302: Based on user ciphertext E U-E Calculate the timestamp TS1 in the middle. The second factor verification is performed. If it is a strict authentication, the user's trust level is strictly compared to check whether the user has omitted any authentication factors before the third factor verification is performed.

[0035] S303: After successful verification, generate the current timestamp TS2 and encrypt it using the user terminal's public key to obtain the user's ciphertext. And calculate the message verification code MAC. E -U=H(TS2||E E -U);

[0036] S304: Transmit timestamp TS2, user ciphertext E E -U and Message Verification Code (MAC) E -U is sent back to the user terminal, and the user terminal performs the first two factors verification as well.

[0037] S305: After the user terminal successfully completes two-factor authentication, the user terminal uses the Chebyshev chaotic mapping value of the edge computing server as a parameter, the user terminal's private key as the order, and a large prime number P2 to calculate the session key.

[0038] And calculate the intermediate value

[0039] S306: Generate timestamp TS3, ciphertext With message verification code MAC U-E2 =H(TS3||SK||E) U-E2 ), timestamp TS3, ciphertext E U-E2 With MAC U-E2 Send to the edge server;

[0040] S307: The edge server uses the user terminal's private key to encrypt the E... U-E2 Decryption is performed, and after verifying the validity of the timestamp, the session key is calculated based on the intermediate value. And verify the message verification code based on the session key SK′ This completes the negotiation of the session key SK1;

[0041] S308: The edge computing server uses the computed session key to process the intermediate value and the ciphertext E. U-E2 Encrypt the key and send it to the user to prove that you have calculated the session key.

[0042] S309: The edge computing server stores the session key SK and the user terminal authentication behavior during the current authentication process in the cloud storage server through a secure channel, and uses the session key SK as the session key for the user terminal's subsequent ride-hailing application.

[0043] In a preferred embodiment of this application, step S4 includes:

[0044] S401: The edge computing server schedules the nearest idle intelligent and autonomous vehicles around the user terminal and generates a timestamp TS4.

[0045] S402: Using the public key for intelligent and autonomous vehicles For timestamp TS4, session key SK, and user digital certificate Encryption is performed to obtain ciphertext.

[0046] S403: Calculate message verification code Then, the timestamp TS4 and the ciphertext E E-C With message verification code MAC E-C Send to intelligent and autonomous vehicles.

[0047] S404: Intelligent and autonomous vehicles use a private key to ciphertext E E-C Decryption is performed, the timestamp validity is verified, and the session key SK is used with the ciphertext E.E-C Calculate the message verification code (MAC) E-C ;

[0048] S405: Generate a timestamp TS5, encrypt it using the session key SK, and obtain the ciphertext.

[0049] and timestamp TS5 with ciphertext E C-M Send to the edge computing server;

[0050] S406: Edge computing server transmits encrypted E C-M Decryption is performed.

[0051] As a preferred embodiment of this application, in step S5, the method includes:

[0052] S501: User terminals and intelligent and autonomous vehicles use session key SK1 for mutual authentication.

[0053] S502: Intelligent and autonomous vehicles send user authentication behavior data and TS5 via session keys to the edge server to update the user trust score and update the session key SK. new =H(sK′||TS5);

[0054] S503: The user updates the session key SK′ in the background based on the timestamp TS5. new =H(SK||TS5).

[0055] As a preferred embodiment of this application, the method further includes:

[0056] Users are categorized into high-risk users, regular users, and premium users;

[0057] Risky users differ from new users in that they require their real identity information to be encrypted in ciphertext during mutual authentication with edge servers. In, among them, This refers to a new digital certificate issued by TA to a high-risk user; that is, a new digital certificate that a user is required to reapply for when they are identified as a high-risk user.

[0058] F stands for Re-authentication Identifier, indicating that the user has been re-authenticated through TA and issued a new digital certificate. In addition to encrypting the timestamp and digital certificate using the session key, a message verification code also needs to be calculated. Perform auxiliary authentication;

[0059] Regular users differ from new users in that they already possess a session key and need to use the updated session key to authenticate with the edge server: the user generates a current timestamp (TS7), encrypts the digital certificate and timestamp using the session key, and obtains ciphertext. The ciphertext is sent to the edge server, which decrypts it using the updated session key, generates a timestamp TS8, and then sends the ciphertext... Timestamp TS8, Edge Server Identity Authentication The updated session key is encrypted and sent to ordinary users for authentication.

[0060] Premium users differ from ordinary users in that they only need to use the session key to encrypt the timestamp to calculate the ciphertext during authentication, without the need for digital certificates and message verification codes to assist in authentication.

[0061] This application also provides a multi-level user anonymity security authentication system based on a game theory trust evaluation mechanism. The multi-level user anonymity security authentication method based on the aforementioned game theory trust evaluation mechanism includes:

[0062] The ciphertext generation module is used to generate matching user information based on the ride-hailing request from the registered user terminal and encrypt the user information using the public key of the registered edge computing server to generate user ciphertext.

[0063] The information acquisition module is used to decrypt the user's ciphertext using the edge server key to obtain user information;

[0064] The verification processing module is used to complete multi-factor authentication and negotiate a session key by verifying the validity of the timestamp, and then store the session key in the cloud storage server and use it as the session key for the user terminal to make subsequent ride-hailing applications;

[0065] The vehicle processing module is used to dispatch the nearest available registered intelligent and autonomous vehicles around the passenger terminal and encrypt the session key and user information using the public key of the intelligent and autonomous vehicles.

[0066] The communication module is used to perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using a session key, and to update the user trust score and session key after authentication so that subsequent communication can be carried out using the session key.

[0067] In some embodiments of this application, this application also relates to a computer storage medium storing a computer program, which is executed by a processor to implement the above-described multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism.

[0068] In some embodiments of this application, this application also relates to a computer, including the aforementioned computer storage medium.

[0069] The technical solution described in this application has the following advantages over the prior art:

[0070] This application achieves a dynamic balance between security and user experience by modeling the interaction behavior between users and edge authentication servers. This application regards each authentication process as a two-subject game scenario, in which the user utility function is composed of authentication convenience (operational complexity, latency) and authentication success probability, with the goal of maximizing its own benefits (i.e., low operation cost and high success rate); the edge server's goal is to minimize authentication risks (such as the probability of malicious behavior penetration) while optimizing system resource consumption.

[0071] This application's design protocol does not place the entire calculation process on an edge server or central node when calculating trust scores. Instead, it adopts homomorphic encryption, whereby the edge server preprocesses and performs local calculations on user behavior data for different authentication factors, homomorphically encrypts each data point, and digitally signs the encryption result using the edge server's private key before transmitting it to the TA (Trust Provider). The TA then performs aggregate calculations without decrypting individual data points, updates the trust score based on game theory according to the user's historical trust scores, and ensures the privacy and data security of the user's trust score. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0073] Figure 1 This is a flowchart of the multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism provided in the embodiments of this application.

[0074] Figure 2 This is a schematic diagram of the overall network architecture provided in the embodiments of this application.

[0075] Figure 3 This is a timing diagram of passenger terminal registration provided in an embodiment of this application.

[0076] Figure 4 This is a timing diagram of edge computing server registration provided in an embodiment of this application.

[0077] Figure 5 This is a timing diagram of intelligent and autonomous vehicle registration provided in an embodiment of this application.

[0078] Figure 6 This is a timing diagram of the first interaction between the user terminal and the edge server provided in the embodiments of this application.

[0079] Figure 7This is a timing diagram of the second interaction between the user terminal and the edge server provided in the embodiments of this application.

[0080] Figure 8 This is a timing diagram showing the interaction between the edge server and intelligent and autonomous vehicles provided in the embodiments of this application. Detailed Implementation

[0081] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0082] This application includes a game theory-based trust evaluation mechanism, privacy protection, and anonymous authentication.

[0083] Among these, a game-theory-based trust evaluation mechanism addresses a pressing issue in the current authentication system: high-quality users do not receive preferential treatment compared to ordinary users during the identity verification process, and both must undergo the same authentication time. To optimize user experience and effectively differentiate between high-quality, ordinary, and high-risk users, we propose a game-theory-based trust evaluation mechanism. This mechanism aims to ensure that high-quality users enjoy a highly efficient service experience with ultra-low latency during the authentication process by accurately measuring and analyzing the trust of different user groups, thereby achieving rational resource allocation and a significant improvement in user experience. This method not only emphasizes the quantitative evaluation of individual trust value but also strives to build a fairer, more transparent, and more efficient authentication environment.

[0084] Privacy protection involves using homomorphic encryption when calculating trust scores. At the edge computing node, user behavior data for different authentication factors is preprocessed and locally calculated. Each data point is then homomorphically encrypted, and the encryption result is digitally signed using the edge server's private key before being transmitted to the TA (Trust Analyst). The TA performs aggregate calculations without decrypting individual data points, thereby updating the trust score based on game theory, thus ensuring the privacy and data security of the user's trust score.

[0085] Anonymous authentication involves issuing an anonymous digital certificate to each user upon registration. This certificate contains false identity information rather than the real identity. During the authentication process, users only display the false identity information through the digital certificate and zero-knowledge proofs, thereby avoiding the risk of identity association.

[0086] In a game theory framework, users face two strategy choices:

[0087] The integrity certification strategy strictly adheres to the certification level defined by its historical behavior, provides factor certification combinations as required, and ensures that the certification process is consistent with the trust level.

[0088] Impersonation authentication strategies attempt to reduce operational costs by forging high-trust identities for authentication, but they carry the risk of being detected.

[0089] Edge servers also face two strategy choices:

[0090] A strict authentication strategy is implemented, comparing users' historical authentication records and trust scores, and strictly authenticating them according to their trust rating level.

[0091] The basic authentication strategy only verifies the basic legitimacy of authentication factors (such as password correctness and device identifier matching) and does not perform historical behavior correlation analysis.

[0092] The protocol designed in this application aims to use a combination of game theory, Chebyshev chaotic mapping and elliptic curve cryptography, zero-knowledge proof and homomorphic encryption to achieve data security and privacy protection for intelligent and autonomous vehicle services in the Internet of Vehicles environment.

[0093] Game theory, a mathematical framework for studying strategic decision-making, focuses on analyzing the behavioral choices of multiple rational participants in the interaction of interests. In such behaviors, each party in a struggle or competition has different goals or interests. To achieve their goals and interests, each party must consider the various possible actions of their opponents and strive to choose the most advantageous or reasonable option. In identity authentication, game theory is applied by treating the authentication process as a repeated game. Users can choose "honest authentication" or "attempted spoofing authentication." "Honest authentication" represents "cooperation," while "attempted spoofing authentication" represents "betrayal." Different strategies bring different benefits to users, and the choice lies in balancing the convenience of successful authentication with being detected as "betrayed" by the system, thus tightening authentication. A reward mechanism and a penalty mechanism are introduced. The reward mechanism is that users who repeatedly "cooperate" and pass the authentication server's check receive high rewards, while the penalty mechanism is that users who attempt "attempted spoofing authentication" are detected as "betrayed" and punished. The final strategy varies depending on the game's outcome.

[0094] The Chebyshev Chaotic Map is a chaotic system based on Chebyshev polynomials, commonly used in cryptography, information security, and random number generation. Its core idea is to generate sequences with chaotic properties through iterative Chebyshev polynomial generation, combining the determinism of mathematics with the unpredictability of chaos to achieve efficient and secure dynamic behavior. The cosine of the Chebyshev Chaotic Map is defined as T. n(x) = cos(n·arccos(x)) mod p, where,

[0095] n∈Z * Let x ∈ (-1, +1), p be a large prime number, n be the order, and x be the Chebyshev chaos parameter. The recurrence relation is T. n (x)=(2xT n-1 (x)-T n-2 (x) mod p, which, based on the semigroup commutative property, yields the formula T. m (T n (x))=cos(m·arccos(cos(n·arccos(x))))=cos(mn·arccos(x))=T mn (x), due to the difficulty in solving its discrete logarithm, that is: knowing T n Given x, a large prime number p, and n, finding the value of n is difficult with current polynomial-time algorithms; the Diffie-Hellman problem refers to: even if T is known... n (x), T m Given x and x, solving for Tmn(x) is difficult. It possesses properties such as initial value sensitivity, pseudo-randomness, and irreversibility.

[0096] Elliptic Curve Cryptography (ECC) uses a base point G(X,Y), selects a large prime number p, and uses a private key k. The public key is used to calculate K = k * G. P (X,Y). Because the operations of the elliptic curve group (GF(p)) involve point addition rather than simple scalar multiplication, its geometric properties make it difficult to directly apply algebraic methods. The order of the group is usually a large prime number, reducing the effectiveness of decomposition attacks such as Pohlig-Hellman. Currently, the best known algorithm (such as Pollard's Rho) has a time complexity of O(√n), requiring exponential computation. In contrast, traditional DLP has sub-exponential time algorithms (such as the number field sieve), while the discrete logarithm problem of elliptic curves (ECDLP) has not seen similar breakthroughs. Therefore, ECC is difficult to solve in polynomial time.

[0097] Zero-knowledge proofs (ZKPs) are cryptographic protocols that allow one party (the prover) to prove the truth of a statement to another party (the verifier) ​​without revealing any specific information about proving the statement. At its core, they achieve three key properties: integrity (an honest prover can convince the verifier), reliability (a fraudster cannot deceive the verifier), and zero-knowledge (the verifier cannot obtain additional information beyond the truth of the statement). For example, a prover can prove to a verifier that "I know a secret" without revealing the secret itself, or verify the validity of a transaction without exposing the transaction details.

[0098] Homomorphic encryption allows direct computation on encrypted data, and the decrypted result is identical to the result of performing the same operation on the plaintext, thus achieving the privacy goal of "data usable but not visible." Its core principle is based on mathematical problems (such as the Learning on Rings (RLWE) problem in lattice ciphers). Encryption maps plaintext to a specific mathematical space, enabling the ciphertext to support operations such as addition and multiplication within that space. The decrypted ciphertext is then equivalent to the direct computation result of the plaintext.

[0099] In autonomous driving scenarios, users send authentication requests to the edge server based on their trust level. Users then choose between "honest authentication" or "impersonation authentication" strategies based on a game theory approach. "Honest authentication" involves users submitting authentication factors according to their trust level; "impersonation authentication" involves users attempting to impersonate a high-level user, submitting fewer authentication factors to reduce authentication latency.

[0100] The edge server chooses between "strict authentication" or "basic authentication" strategies for user authentication requests based on a game theory approach. "Strict authentication" means that the edge server strictly compares the user's trust level and authenticates the user's identity according to that trust level; "basic authentication" means that the edge server processes the authentication request submitted by the user and authenticates the user only based on the authentication factor submitted by the user.

[0101] In the game between these two strategies, a hybrid game model and Bayesian update mechanism from game theory are used, combined with user historical behavior statistics, to construct the following trust scoring function:

[0102]

[0103] Among them, S t L represents the trust score for the current behavior. k L represents the level of trust based on trust scores. k Values ​​range from 1 to 3; This represents the rating coefficient for the current behavior, also known as L. k The expected payoff value at each level is specifically calculated from the expected payoff in the mixed game model; With L k The same value indicates the number of verification factors required for different certification levels; E max,i E represents the maximum number of input errors for the i-th factor within the timestamp validity range. max,i ≤3; e i This represents the number of input errors for the i-th factor, 0 ≤ e i ≤E max,i ; The values ​​of k, in descending order, are 0.1, 0.15, and 0.2, representing the authentication failure penalty coefficients for different authentication levels. For recent authentication errors, ω is the time decay coefficient, and N is the penalty. last_time This refers to the number of authentication attempts between the current authentication attempt and the previous authentication failure.

[0104] Users who consistently employ a "trustworthy authentication strategy" will gradually improve their authentication level. However, repeatedly using a "spoofing authentication strategy" will inevitably be exposed during a detection, lowering the trust rating and leading to a more cumbersome authentication process. Edge servers implement defense through a probability sampling detection mechanism, targeting users of different levels with preset probabilities. Perform deep and rigorous authentication on user requests, based on probability. Only basic authentication is performed on user authentication requests. The expected payoffs of the hybrid game model based on this are shown in the table below:

[0105] Table 1. Payoff Table for Hybrid Game Model

[0106]

[0107] The hybrid game model designed in this application shows the expected payoffs between the two entities involved in the authentication process, as shown in Table 1. Here, x represents the probability of user integrity authentication. Indicates the edge server's support for L k The probability of strict authentication for users of different user levels is set based on the user level settings. The difference is that high-quality users are less likely to be subject to strict verification, while high-risk users are more likely to be subject to strict verification. This is the setting. Indicates pressing L k The time delay required for factor authentication at the level (i.e., according to L) k For users of a certain level, authentication should be performed by submitting authentication factors, which requires a delay. x This indicates the latency required for authentication when a user is impersonating another user.

[0108] Each strategy has a corresponding expected return, and edge servers in Under probabilistic strict authentication, when a user chooses a trustworthy authentication strategy, the expected benefit of the edge server refers to the time required for authentication. The latency, the user's expected benefit is in the calculation of their trust scoring function. During strict authentication at the edge server, if a user is detected to have performed integrity authentication based on their trust level, the reward for the user's trust score will increase significantly. The edge server will then verify the authentication factor submitted by the user, with a latency equal to the latency required to verify the authentication factor at that level.

[0109] Edge servers in Under probabilistic basic authentication, when a user selects a trustworthy authentication strategy, the expected benefit of the edge server refers to the cost of authentication. The time delay, and the expected benefit of the user is when calculating its trust scoring function The edge server Executes strict authentication with a probability. At this time, when the user selects the spoof authentication strategy, the expected benefit of the edge server refers to the time delay it needs for authentication The time delay, and the expected benefit of the user is when calculating its trust scoring function Among them, when the edge server performs strict authentication and detects that the user does not authenticate according to its trust level but adopts the spoof authentication strategy, the penalty for the user's trust score increases. The edge server not only needs to verify the authentication factors submitted by the user but also requires the user to resubmit the authentication factors at the true level according to strict standards for authentication. The time delay is the time delay required to verify the factors submitted by the user and the authentication of the true level factors. The edge server Executes basic authentication with a probability. At this time, when the user selects the spoof authentication strategy, the expected benefit of the edge server refers to the time delay T it needs for authentication x The time delay, and the expected benefit of the user is when calculating its trust scoring function

[0110] The user's selection of different strategies will bring different benefits to itself, that is, different Affects the calculation of the trust score, and the trust score determines the user's trust level L k , which will in turn affect the probability of the edge server's different authentication strategies for the user.

[0111] Based on the trust score calculation established by the above game theory, authenticate the authentication factors submitted by the user for different strategies. During the authentication process, based on the user's trust score, it is divided into three levels: high-quality users, ordinary users, and risk users. Classifying users, for high-trust-score users, only simple authentication is required, greatly reducing the computational delay required for authentication.

[0112] For high-quality users, due to their long-term high trust score, that is, the trust score is higher than the threshold b, only the session key and timestamp updated after the previous authentication are authenticated, and no additional auxiliary authentication is required.

[0113] For ordinary users, that is, the trust score is between the thresholds a and b (a < b), considering that there may have been multiple authentication errors in their history, on the basis of authenticating the updated session key, timestamp and digital certificate authentication are performed. If it is a user who has just completed initialization, mutual authentication between the public and private keys and the edge server is required, and message authentication code verification is performed, and then the session key is negotiated for communication.

[0114] For risk users, that is, the trust score is lower than the threshold a, they need to apply to TA for the issuance of a new digital certificate

[0115] The "F" indicates a re-authentication process, signifying that the user has been re-authenticated via TA and issued a new digital certificate. This authentication process requires the use of a verification code and the provision of the digital certificate and timestamp.

[0116] The specific process of the protocol designed in this application is referenced. Figure 1 As shown, the overall network architecture of this application is based on... Figure 2 As shown; therefore, the specific process of each step of the agreement involved in this application is as follows:

[0117] refer to Figure 3 As shown; 1.1: User U i For each user (i∈1,+∞), the user registers through the APP at the registration center. The Trusted Authority Center (TA) checks the user's identity using facial biometrics and phone number. If the identity does not exist, a user identity is generated based on the user's phone number. random numbers Using the user's private key, and selecting large prime numbers P1 and P2 and the elliptic curve base point G, the user's public key is calculated. Issue digital certificates to newly registered users For the XOR operation, initialize its trust score to b, and then... The registration result is returned to the user via a secure channel, and the TA stores the user's relevant information. This is public information.

[0118] refer to Figure 4 As shown in Figure 1.2: The edge computing service registers with the TA, and the TA generates an identity code I for the edge computing server. random numbers As the private key of the edge computing server, calculate the public key. Chebyshev chaotic mapping code

[0119] in, Representative with For order, The Chebyshev chaotic mapping value of the parameter. This means identifying the edge server. Using hash calculations and naturally connecting them to the public key, relevant information for the edge server is stored. Send to the edge computing server via a secure channel. This is public information.

[0120] refer to Figure 5 As shown in Figure 1.3: Intelligent and autonomous vehicles register in the TA (Task Authority), and the TA generates [a system for] intelligent and autonomous vehicles. random numbers As the private key for intelligent and autonomous vehicles, appropriate edge computing servers are allocated based on the operating service area of ​​the intelligent and autonomous vehicles to calculate the public key for the intelligent and autonomous vehicles. Store information related to intelligent and autonomous vehicles, and Send to intelligent and autonomous vehicles via a secure channel. This is public information.

[0121] The public keys are all public, while the private keys and Chebyshev chaotic mapping values ​​are kept secret.

[0122] refer to Figures 6-8 As shown; New users:

[0123] 2.1: When a newly registered user sends a ride request to the edge server for the first time through the APP: Generate a current timestamp TS1, and send the digital certificate, timestamp TS1, and edge computing server public key. Encryption is performed to obtain ciphertext.

[0124] ENC is the encryption method, and the SHA256 hash is used to calculate the message verification code (MAC). U-E =H(TS1||E U-E ), timestamp TS1, ciphertext E U-E With message verification code MAC U-E Send to the edge computing service node.

[0125] 2.2: The edge server calculates the ciphertext E using its own key according to the formula used during the registration phase of the public key calculation. U-E Decrypt to obtain DEC stands for decryption. The system selects between a strict authentication strategy and a basic authentication strategy based on probabilities in the hybrid game model. If a strict authentication strategy is used, a data request is sent to the TA (User Accreditation Provider) based on the obtained user digital certificate. The user information stored in the TA is obtained through a secure channel, and the system compares the user's historical authentication records and trust level, strictly verifying the correctness and completeness of authentication factors according to the trust level. If a basic authentication strategy is used, only the basic legality of the authentication factors is verified, without performing historical behavior correlation analysis.

[0126] 2.3: After obtaining user information, determine the validity of the timestamp in advance. Among them, T cur1 For the current time, perform first-factor verification; calculate based on the timestamp in the ciphertext.

[0127] Perform a second-factor authentication; if it is strict authentication, strictly compare the user's trust level to check if the user has omitted any authentication factors, and then perform a third-factor authentication. After successful authentication, generate the current timestamp TS2, encrypt it with the user's public key, and obtain the ciphertext.

[0128] And calculate the message verification code MAC. E-U =H(TS2||E E-U ), timestamp TS2, ciphertext E E-U With message verification code MAC E-U The message is sent back to the user, who then performs the same verification as the first two factors.

[0129] 2.4: After successful verification, the user negotiates the session key SK1 with the edge server. The user calculates the session key using the Chebyshev chaotic mapping value of the edge computing server as a parameter, their own private key as the order, and a large prime number P2.

[0130] And calculate the intermediate value Generate timestamp TS3, ciphertext With message verification code MAC U-E2 =H(TS3||SK||E) U-E2 ), timestamp TS3, ciphertext E U-E2 With MAC U-E2 The ciphertext is sent to the edge server. Upon receiving the ciphertext, the edge server first decrypts it using its private key, and after verifying the validity of the timestamp, calculates the session key based on the intermediate value.

[0131] Verify the message verification code based on the calculated session key.

[0132] At this point, the session key SK1 has been successfully negotiated.

[0133] 2.5: The computational server uses the calculated session key to process the intermediate value and the ciphertext E. U-E2 The session key is encrypted and sent to the user to prove that the server has calculated it. The edge computing server stores the session key SK along with the user's authentication behavior during the current authentication process in a secure channel to the cloud storage server. Subsequent ride-hailing requests from the user will use the session key SK negotiated in this transaction.

[0134] 2.6: The edge computing server schedules the nearest available intelligent and autonomous vehicles around the user, generates a timestamp TS4, and uses the public key of the intelligent and autonomous vehicle. For timestamps, session keys, and user digital certificates Encryption is performed to obtain ciphertext. Calculate message verification code Timestamp TS4, Ciphertext E E-C With message verification code MAC E-C Send to intelligent and autonomous vehicles. The intelligent and autonomous vehicles use their private key to decrypt the ciphertext, verify the timestamp's validity, and calculate a message verification code using the session key and the ciphertext. A timestamp TS5 is generated, encrypted using the session key, to obtain the ciphertext. Combine the timestamp TS5 with the ciphertext E C-M The encrypted message is sent to the edge computing server, which decrypts it and determines whether the intelligent and autonomous vehicle has received the session key used for communication with the user.

[0135] 2.7: Users and intelligent and autonomous vehicles use session keys (SK) for mutual authentication.

[0136] 2.8: After authentication is completed, intelligent and autonomous vehicles send user authentication behavior data and TS5 via session key to the edge server to update the user trust score and update the session key.

[0137] SK new =H(SK′||TS5).

[0138] 2.9: After authentication is complete, the user updates the session key in the background based on the TS5 timestamp.

[0139] SK′ new =H(SK||TS5).

[0140] High-risk users: Unlike new users, high-risk users require their real identity information to be encrypted in ciphertext during mutual authentication with edge servers. In, among them, This refers to the new digital certificate issued by TA to a risky user (i.e., the new digital certificate that a user is required to reapply for when they are identified as a risky user).

[0141] Here, F stands for Re-authentication Identifier, indicating that the user has been re-authenticated via TA and issued a new digital certificate. In addition to encrypting the timestamp and digital certificate using the session key, a message verification code also needs to be calculated. Perform auxiliary authentication.

[0142] Regular users: Unlike new users, these users already have session keys and need to use the updated session keys to authenticate with the edge server.

[0143] (2.1-2.4): The user generates the current timestamp TS7, and uses the session key to encrypt the digital certificate and the timestamp to obtain ciphertext. The ciphertext is sent to the edge server, which decrypts it using the updated session key, generates a timestamp TS8, and then sends the ciphertext... Timestamps, edge server identity identifiers The updated session key is encrypted and sent to the passenger for authentication.

[0144] Premium users: Unlike regular users, they only need to use the session key to encrypt the timestamp to calculate the ciphertext during authentication, without the need for digital certificates and message verification codes to assist in authentication.

[0145] In summary, the meanings of all the letter codes are as follows:

[0146] Edge servers, identification systems for intelligent and autonomous vehicles; User pseudo-anonymous digital certificate;

[0147] User, edge server, and private keys for intelligent and autonomous vehicles;

[0148] User, edge server, and public keys for intelligent and autonomous vehicles;

[0149] The edge server Chebyshev value is used to calculate the session key;

[0150] H(*): Hash calculation; G p ECC modulo P1; TS: timestamp;

[0151] E: Ciphertext; MAC: Message Verification Code; T cen Intermediate value for session key calculation.

[0152] In some embodiments of this application, this application also provides a multi-level user anonymity security authentication system based on a game theory trust evaluation mechanism. The multi-level user anonymity security authentication method based on the above-described game theory trust evaluation mechanism includes:

[0153] The ciphertext generation module is used to generate matching user information based on the ride-hailing request from the registered user terminal and encrypt the user information using the public key of the registered edge computing server to generate user ciphertext.

[0154] The information acquisition module is used to decrypt the user's ciphertext using the edge server key to obtain user information;

[0155] The verification processing module is used to complete two-factor authentication and negotiate a session key by verifying the validity of the timestamp, and then store the session key in the cloud storage server and use it as the session key for subsequent ride-hailing applications by the user terminal.

[0156] The vehicle processing module is used to dispatch the nearest available registered intelligent and autonomous vehicles around the passenger terminal and encrypt the session key and user information using the public key of the intelligent and autonomous vehicles.

[0157] The communication module is used to perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using a session key, and to update the user trust score and session key after authentication so that subsequent communication can be carried out using the session key.

[0158] In some embodiments of this application, this application also relates to a computer storage medium storing a computer program, which is executed by a processor to implement the above-described multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism.

[0159] In some embodiments of this application, this application also relates to a computer, including the aforementioned computer storage medium.

[0160] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0161] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A multi-level user anonymity security authentication method based on game theory trust evaluation mechanism, characterized in that, Includes the following steps: S1: Based on the ride-hailing request from the registered user terminal, generate matching user information and encrypt the user information using the public key of the registered edge computing server to generate user ciphertext; S2: Decrypt the user's ciphertext using the edge server key to obtain user information; S3: Complete two-factor authentication and negotiate a session key by verifying the validity of the timestamp, and then store the session key in the cloud storage server and use it as the session key for the user terminal's subsequent ride-hailing application; S4: Dispatch the nearest available registered intelligent and autonomous vehicle around the passenger terminal and encrypt the session key and user information using the public key of the intelligent and autonomous vehicle; S5: Use session keys to perform mutual authentication between the user terminal and intelligent and autonomous vehicles, and update the user trust score and session key after authentication so that the session key can be used for subsequent communication. When a user terminal registers with the registration center, the method includes: S101: When the Trusted Authority Center (TA) checks that the user terminal's identity does not exist through facial biometrics and phone number verification, it generates a user identity for the user terminal based on the user terminal's phone number. And random number As the user's private key; S102: Select large prime numbers P1 and P2 and the elliptic curve base point G, and calculate the user terminal public key. ,in, The ECC is modulo a large prime number P1; S103: Issue digital certificates to newly registered user terminals ,in, For hash calculation, The XOR operation initializes its trust score to b; then... The registration result is returned to the user terminal via a secure channel, and the TA stores relevant information about the user terminal. This is public information; When an edge computing server registers with a registry center, the method includes: S111: Trusted Authority Center (TA) generates identity codes for edge computing servers. And random number As the private key for the edge computing server; S112: Compute the public key for the edge computing server ; S113: Chebyshev chaotic mapping code for computing edge servers ,in, Representative with For order, The Chebyshev chaotic mapping value of the parameter. This means identifying the edge server. Use hash calculations and naturally connect them to the public key; S114: Store edge server related information and , Send to the edge computing server via a secure channel. This is public information.

2. The multi-level user anonymity security authentication method based on game theory trust evaluation mechanism according to claim 1, characterized in that, When intelligent and autonomous vehicles register with the registry center, the method includes: S115: Trusted Authority Center (TA) generates identification codes for intelligent and autonomous vehicles. And random number As a private key for intelligent and autonomous vehicles; S116: Allocate matching edge computing servers based on the operating service area of ​​intelligent and autonomous vehicles; S117: Computational Intelligence and Public Keys for Autonomous Vehicles ; S118: Stores information related to intelligent and autonomous vehicles and will Send to intelligent and autonomous vehicles via a secure channel. This is public information.

3. The multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism according to claim 2, characterized in that, In step S1, the method includes: S121: Generate the current timestamp TS1 based on the first ride-hailing request sent by the registered user terminal to the edge computing server; S122: Use the digital certificate and timestamp TS1 with the edge computing server's public key. Encryption is performed to obtain the user's ciphertext. And use the SHA256 hash to calculate the message verification code. ENC is the encryption method; S123: Transfer timestamp TS1, ciphertext With message verification code Send to the edge computing service node.

4. The multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism according to claim 3, characterized in that, In step S2, the method includes: S201: Based on the public key calculation formula used by the edge server during the registration phase, decrypt the user's ciphertext using the edge server's key to obtain... DEC stands for decryption; S202: Based on the probability in the hybrid game model, choose to implement either a strict authentication strategy or a basic authentication strategy. If the strict authentication strategy is adopted, a data request is sent to the TA based on the obtained user digital certificate. The user information stored in the TA is obtained through a secure channel. The user's historical authentication records and trust level are compared, and the authentication factors are strictly verified to ensure that they are correct and without omissions according to the trust level. If the basic authentication strategy is adopted, only the basic legality of the authentication factors is verified, and no historical behavior correlation analysis is performed.

5. The multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism according to claim 4, characterized in that, In step S3, the method further includes: S301: After obtaining user information, determine the validity of the timestamp. First-factor verification was performed; among them, T cur1 ΔT represents the current time and the effective time interval. S302: Based on user ciphertext Middle timestamp ,calculate If it is a strict authentication, the user's trust level will be strictly compared to check if the user has omitted any authentication factors, and then a third factor verification will be performed. S303: After successful verification, generate the current timestamp TS2 and encrypt it using the user terminal's public key to obtain the user's ciphertext. And calculate the message verification code. ; S304: Contain timestamp TS2 and user ciphertext With message verification code The message is sent back to the user terminal, where the user terminal also performs the first two factors verification. S305: After the user terminal successfully completes two-factor authentication, the user terminal uses the Chebyshev chaotic mapping value of the edge computing server as a parameter, the user terminal's private key as the order, and a large prime number P2 to calculate the session key. And calculate the intermediate value ; S306: Generate timestamp TS3, ciphertext With message verification code , timestamp TS3, ciphertext and Send to the edge server; S307: The edge server uses the user terminal's private key to ciphertext. Decryption is performed, and after verifying the validity of the timestamp, the session key is calculated based on the intermediate value. And based on the session key Verification message verification code This completes the negotiation of the session key SK; S308: The edge computing server uses the calculated session key to process the intermediate value and ciphertext. Encrypt the key and send it to the user to prove that you have calculated the session key. S309: The edge computing server stores the session key SK and the user terminal authentication behavior during the current authentication process in the cloud storage server through a secure channel, and uses the session key SK as the session key for the user terminal's subsequent ride-hailing application.

6. The multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism according to claim 5, characterized in that, In step S4, the method includes: S401: The edge computing server schedules the nearest idle intelligent and autonomous vehicles around the user terminal and generates a timestamp TS4. S402: Using the public key for intelligent and autonomous vehicles For timestamp TS4, session key SK, and user digital certificate Encryption is performed to obtain ciphertext. ; S403: Calculate message verification code This will then combine the timestamp TS4 and the encrypted data. With message verification code Send to intelligent and autonomous vehicles; S404: Intelligent and autonomous vehicles use private keys to ciphertext. Decryption is performed, the timestamp validity is verified, and the session key SK is used with the ciphertext. Calculate message verification code ; S405: Generate a timestamp TS5, encrypt it using the session key SK, and obtain the ciphertext. Combine the timestamp TS5 with the ciphertext Send to the edge computing server; S406: Edge computing server for encrypted data Decryption is performed.

7. A multi-level user anonymity security authentication method based on a game theory trust evaluation mechanism according to claim 6, characterized in that, In step S5, the method includes: S501: User terminals and intelligent and autonomous vehicles use session keys SK for mutual authentication. S502: Intelligent and autonomous vehicles send user authentication behavior data and TS5 via session keys to the edge server to update the user trust score and update the session key. ; S503: The user updates the session key in the background based on the timestamp TS5. .

8. The multi-level user anonymity security authentication method based on game theory trust evaluation mechanism according to claim 7, characterized in that, The method further includes: Users are categorized into high-risk users, regular users, and premium users; Risky users differ from new users in that they require their real identity information to be encrypted in ciphertext during mutual authentication with edge servers. In, among them, This refers to a new digital certificate issued by TA to a high-risk user; that is, a new digital certificate that a user is required to reapply for when they are identified as a high-risk user. F stands for Re-authentication Identifier, indicating that the user has been re-authenticated through TA and issued a new digital certificate. In addition to encrypting the timestamp and digital certificate using the session key, a message verification code also needs to be calculated. Perform auxiliary authentication; Regular users differ from new users in that they already possess a session key and need to use the updated session key to authenticate with the edge server: the user generates the current timestamp. The digital certificate and timestamp are encrypted using the session key to obtain the ciphertext. The ciphertext is sent to the edge server, which decrypts it using the updated session key, generates a timestamp TS8, and then sends the ciphertext... TS8 timestamp, edge server identity identifier The updated session key is encrypted and sent to ordinary users for authentication. Premium users differ from ordinary users in that they only need to use the session key to encrypt the timestamp to calculate the ciphertext during authentication, without the need for digital certificates and message verification codes to assist in authentication.

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