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

Abstract

The invention discloses a multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, and the method comprises the steps: building a Nash equilibrium model of a user and a system based on the game theory, enabling an edge server to carry out the strategy selection based on the user trust level design probability in authentication strength, solving a static rule problem in dynamic risk assessment, and improving the security of the user. An edge server and a user are allowed to form a dynamic game cycle, the limitation of one-way evaluation is solved, and coevolution of a defense strategy and a user behavior is realized; an incentive mechanism is introduced when a trust scoring function is designed, a user is guided to actively maintain a high trust state, and a one-way punishment mechanism of dynamic risk assessment is supplemented. In order to protect data privacy, trust score calculation is carried out step by step, data preprocessing and local calculation are carried out on an edge server, local calculation results of different authentication factor behavior data are subjected to homomorphic encryption and public key signature and are sent to a TA, aggregation calculation is carried out on the local calculation results, and trust scores are updated according to historical trust scores of users.

Description

Technical Field

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

[0002] In the existing identity authentication process, the dynamic risk assessment method is mostly used to classify users. Machine learning algorithms are used to analyze user behavior and environmental context information in real time, and the authentication level is automatically adjusted. However, this method will ignore the user's behavior strategy. For example, users may deliberately avoid authentication, and the existing method only uses "penalties" to deal with risks, lacking positive incentives for "honest behavior". In addition, the existing dynamic risk assessment method is a one-sided risk scoring of users by the system, without considering the mutual game between the user and the system. The system cannot guide user behavior by dynamically adjusting the authentication strategy, resulting in passive defense.

[0003] Many algorithms for calculating dynamic trust scores are executed on edge computing nodes or central nodes. The technology executed on edge computing nodes does not consider that edge computing nodes are honest and curious nodes (that is, they will strictly execute the set program steps, but there may be attackers who break in and obtain data). The calculated data is stored on edge computing nodes, which may cause the user's trust score to be modified by malicious attackers; while the related technology executed on central nodes stores a large number of computing tasks on central nodes. Although data security is guaranteed, the computing time complexity is not considered, which will bring a heavy computing burden to central nodes.

[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] Object of the Invention: To overcome the above deficiencies, the object of this application is to provide a multi-level user anonymous security authentication method and system based on a game theory trust evaluation mechanism. By modeling the interaction behavior between the user and the edge authentication server, a dynamic balance between security and user experience is achieved, and homomorphic encryption is adopted. On the edge server, the behavior data of the user for different authentication factors is preprocessed and locally calculated. Each data is homomorphically encrypted, and the encrypted result is digitally signed using the private key of the edge server and transmitted to the TA. The TA performs aggregation calculation without decrypting individual data, and updates the trust score based on game theory according to the user's historical trust score, ensuring the privacy protection and data security of the user's trust score.

[0006] To solve the above technical problems, this application provides a multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, including:

[0007] S1: Generate the matching user information according to the car-hailing application of the registered user terminal, and encrypt the user information with the public key of the registered edge computing server to generate a user ciphertext;

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

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

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

[0011] S5: Perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using the session key and update the user trust score and session key after authentication to use the session key for subsequent communication.

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

[0013] S101: When the trusted authority center TA checks that the identity of the user terminal does not exist through face biometrics and phone number, generate a user identity for the user terminal according to the phone number of the user terminal and use the random number as the user private key;

[0014] S102: Select large prime numbers P1, P2 and the elliptic curve base point G and calculate the user terminal public key where is the ECC with the large prime number P1 as the modulus;

[0015] S103: Issue a digital certificate to the newly registered user terminal where H is the hash calculation, ⊕ is the exclusive OR operation, and initialize its trust score to b; then and the registration result is returned to the user terminal through a secure channel. TA stores the relevant information of the user terminal, which is public information.

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

[0017] S111: The trusted authority center TA generates an identity code for the edge computing server and uses the random number as the private key of the edge computing server;

[0018] S112: Calculate the public key of the edge computing server

[0019] S113: Calculate the Chebyshev chaotic mapping code of the edge computing server Wherein, represents the Chebyshev chaotic mapping value with as the order and as the parameter, and is to calculate the identity of the edge server using hash calculation and natural connection with the public key; S114: Store the information related to the edge server and send to the edge computing server through a secure channel, which is public information.

[0020] As a preferred embodiment of the present application, when the intelligent and autonomous vehicle registers with the registration center, the method includes:

[0021] S115: The trusted authority center TA generates an identity code for the intelligent and autonomous vehicle and uses the random number as the private key of the intelligent and autonomous vehicle;

[0022] S116: Allocate a matching edge computing server according to the operation service area of the intelligent and autonomous vehicle;

[0023] S117: Calculate the public key of the intelligent and autonomous vehicle

[0024] S118: Store the information related to the intelligent and autonomous vehicle and send to the intelligent and autonomous vehicle through a secure channel, which is public information.

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

[0026] S121: Generate the current timestamp TS1 according to the car-hailing application sent by the registered user terminal to the edge computing server for the first time;

[0027] S122: Encrypt the digital certificate and the timestamp TS1 with the public key of the edge computing server to obtain the user ciphertext and calculate the message authentication code MACU-E = H(TS1||E U-E ) using the hash SHA256, where ENC is the encryption method.

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

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

[0030] S201: Decrypt the user ciphertext with the edge server key according to the public key calculation formula of the edge server in the registration stage to obtain where DEC is decryption;

[0031] S202: According to the probability in the hybrid game model, select whether to execute the strict authentication strategy or the basic authentication strategy. If it is the strict authentication strategy, send a data request to the TA according to the obtained user digital certificate, obtain the user information stored in the TA through the secure channel, compare the user's historical authentication records and trust levels, and strictly verify whether the authentication factors are correct and complete according to the trust level; if it is the basic authentication strategy, only verify the basic legality of the authentication factors and do not perform historical behavior correlation analysis.

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

[0033] S301: After obtaining the user information, judge the validity of the timestamp for the first factor verification; where T cur1 is the current time, and ΔT is the valid time interval;

[0034] S302: According to the timestamp TS1 in the user ciphertext E U-E calculate for the second factor verification. If it is strict authentication, at this time, strictly compare the user trust level, check whether the user has omitted to submit authentication factors, and perform the third factor verification;

[0035] S303: After the verification passes, generate the current timestamp TS2 and encrypt it with the public key of the user terminal to obtain the user ciphertext and calculate the message authentication code MAC E -U = H(TS2||E E -U);

[0036] S304: Send the timestamp TS2, the user ciphertext E E -U and the message authentication code MAC E -U back to the user terminal, and the user terminal also performs the first two factor verifications;

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

[0038] And calculate the intermediate value

[0039] S306: Generate timestamp TS3, ciphertext And message authentication code MAC U-E2 = H(TS3||SK||E U-E2 ), and send timestamp TS3, ciphertext E U-E2 And MAC U-E2 To the edge server;

[0040] S307: The edge server decrypts the ciphertext E U-E2 Using the private key of the user terminal. After verifying the validity of the timestamp, calculate the session key according to the intermediate value And verify the message authentication code according to the session key SK' Thus completing the negotiation of the session key SK1;

[0041] S308: The edge computing server uses the calculated session key to encrypt the intermediate value and the ciphertext E U-E2 And send it to the user to prove that it has 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 subsequent car-hailing application of the user terminal.

[0043] As a preferred mode of this application, in step S4, the method includes:

[0044] S401: The edge computing server schedules the nearest idle intelligent and autonomous vehicle around the user terminal to generate timestamp TS4;

[0045] S402: Use the public key of the intelligent and autonomous vehicle To encrypt the timestamp TS4, session key SK, and user digital certificate To obtain the ciphertext

[0046] S403: Calculate the message authentication code Furthermore, send the timestamp TS4, ciphertext E E-C And message authentication code MAC E-C To the intelligent and autonomous vehicle.

[0047] S404: The intelligent and autonomous vehicle decrypts the ciphertext E E-C Using the private key, verifies the validity of the timestamp, and uses the session key SK and the ciphertext EE-C Calculate the Message Authentication Code MAC E-C ;

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

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

[0050] S406: The edge computing server decrypts the ciphertext E C-M for decryption.

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

[0052] S501: The user terminal and the intelligent and autonomous vehicle perform mutual authentication using the session key SK1;

[0053] S502: The intelligent and autonomous vehicle sends the user authentication behavior data and TS5 to the edge server through the session key 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′ according to the timestamp TS5 in the background new = H(SK||TS5).

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

[0056] Dividing users into high-risk users, ordinary users and premium users;

[0057] High-risk users are different from new users. When high-risk users authenticate with the edge server, they need to encrypt their real identity information in the ciphertext wherein, is the new digital certificate newly issued by TA for high-risk users, that is, when the user is determined to be a high-risk user, a new digital certificate is required to be reapplied

[0058] where F is the reshaping identifier, indicating that the user has passed the re-authentication by TA and a new digital certificate has been issued. In addition to encrypting the timestamp and digital certificate using the session key, it is also necessary to calculate the message authentication code for auxiliary authentication;

[0059] Ordinary users are different from new users. At this time, the user already has a session key and needs to perform mutual authentication with the edge server using the updated session key: The user generates the current timestamp TS7, encrypts the digital certificate and the timestamp using the session key to obtain the ciphertext Send it to the edge server. The edge server decrypts the ciphertext using the updated session key, generates a timestamp TS8, and sends the ciphertext timestamp TS8 and the edge server identity Encrypt it with the updated session key and send it to the ordinary user for identity authentication;

[0060] Premium users are different from ordinary users. When authenticating, they only need to encrypt the timestamp with the session key to calculate the ciphertext, and do not need to use digital certificates and message authentication codes for auxiliary authentication.

[0061] This application also provides a multi-level user anonymous security authentication system based on a game theory trust evaluation mechanism, which uses the above-mentioned multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, including:

[0062] The ciphertext generation module is used to generate matching user information according to the car-hailing application of the registered user terminal, and encrypt the user information with the public key of the registered edge computing server to generate a user ciphertext;

[0063] The information acquisition module is used to decrypt the user ciphertext with 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 subsequent car-hailing applications of the user terminal;

[0065] The vehicle processing module is used to dispatch the nearest idle registered intelligent and autonomous vehicle around the passenger terminal and encrypt the session key and user information with the public key of the intelligent and autonomous vehicle;

[0066] The communication module is used to perform mutual identity authentication between the user terminal and the intelligent and autonomous vehicle using the session key, and update the user trust score and the session key after authentication to use the session key for subsequent communication.

[0067] In some embodiments of this application, this application also relates to a computer storage medium, on which a computer program is stored, and the computer program is executed by a processor to implement the above-mentioned multi-level user anonymous 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 above-mentioned computer storage medium.

[0069] The above technical solutions of this application have the following advantages compared with the prior art:

[0070] This application realizes the dynamic balance between security and user experience by modeling the interaction behavior between the user and the edge authentication server. This application regards each authentication process as a two-agent game scenario, where the user's utility function is jointly composed of authentication convenience (operation complexity, latency) and authentication passing probability, and the goal is to maximize its own benefits (i.e., low operation cost and high passing rate); the goal of the edge server is to minimize the authentication risk (such as the probability of malicious behavior penetration), and at the same time optimize the system resource consumption.

[0071] When this application designs the protocol to calculate the trust score, it does not place all the calculation processes in the edge server or the central node. Instead, it adopts the method of homomorphic encryption. The edge server preprocesses and locally calculates the user's behavior data for different authentication factors, encrypts each data through homomorphic encryption, and digitally signs the encrypted result using the private key of the edge server, and then transmits it to the TA. The TA performs aggregation calculation without decrypting individual data, and updates the trust score based on game theory according to the user's historical trust score, ensuring the privacy protection and data security of the user's trust score. Brief Description of the Drawings

[0072] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0073] Figure 1 It is the overall flowchart of the multi-level user anonymous security authentication method based on the game theory trust evaluation mechanism provided by the embodiment of this application.

[0074] Figure 2 It is the schematic diagram of the overall network architecture provided by the embodiment of this application.

[0075] Figure 3 It is the timing diagram of passenger terminal registration provided by the embodiment of this application.

[0076] Figure 4 It is the timing diagram of edge computing server registration provided by the embodiment of this application.

[0077] Figure 5 It is the timing diagram of intelligent and autonomous vehicle registration provided by the embodiment of this application.

[0078] Figure 6 It is the timing diagram of the first interaction between the user terminal and the edge server provided by the embodiment of this application.

[0079] Figure 7It is a timing diagram of the second interaction between the user terminal and the edge server provided by the embodiment of the present application.

[0080] Figure 8 It is a timing diagram of the interaction between the edge server and the intelligent and autonomous vehicle provided by the embodiment of the present application. Detailed implementation manners

[0081] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, but should not be construed as limiting the present application.

[0082] The present application includes a game theory trust evaluation mechanism, privacy protection, and anonymous authentication.

[0083] Among them, the game theory trust evaluation mechanism, that is: in the current authentication system, there is an urgent problem that high-quality users do not receive preferential treatment different from that of ordinary users during the identity verification process, and both need to experience the same authentication duration. To optimize the user experience and effectively distinguish user groups of high-quality users, ordinary users, and risk users, we propose a trust evaluation mechanism based on game theory. This mechanism aims to ensure that high-quality users can enjoy an efficient service experience with ultra-low latency in the authentication process through accurate trust measurement and analysis of different user groups, so as to achieve reasonable resource allocation and significant improvement of the user experience. This method not only emphasizes the quantitative evaluation of individual trust values, but also aims to build a more fair, transparent, and efficient authentication environment.

[0084] Among them, privacy protection, that is: when calculating the trust score, homomorphic encryption is adopted. At the edge computing node, the behavior data of users for different authentication factors is preprocessed and locally calculated. Each data is homomorphically encrypted, and the encrypted result is digitally signed using the private key of the edge server and transmitted to the TA. The TA performs aggregation calculation without decrypting individual data, so as to update the trust score based on game theory, ensuring the privacy protection and data security of the user trust score.

[0085] Among them, anonymous authentication, that is: each user is issued an anonymous digital certificate by the TA during registration, and the certificate contains pseudo-identity information instead of the real identity; during the authentication process, the user only shows the pseudo-identity information through the digital certificate and using zero-knowledge proof, thus avoiding the risk of identity association.

[0086] In the game framework, the user faces two strategy choices:

[0087] The integrity authentication strategy strictly follows the authentication level defined by its historical behavior, provides a combined factor authentication as required, and ensures that the authentication process is consistent with the trust level;

[0088] The spoofing authentication strategy attempts to authenticate by forging an identity with a high trust level to reduce its own operation costs, but there is a risk of being detected.

[0089] The edge server also faces two strategy choices:

[0090] The strict authentication strategy compares the user's historical authentication records and trust scores, and authenticates strictly according to its trust evaluation level;

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

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

[0093] Among them, game theory is a mathematical theoretical framework for studying strategic decision-making. Its core lies in analyzing the behavior choices of multiple rational participants in the interaction of interests. In such behaviors, the parties participating in the struggle or competition have different goals or interests. To achieve their respective goals and interests, each party must consider various possible action plans of the opponent and strive to select the most favorable or reasonable plan for itself. The game theory in identity authentication is reflected in regarding the authentication process of both parties as a repeated game. The user can choose "honest authentication" or "attempt to spoof authentication". "Honest authentication" represents "cooperation", and "attempt to spoof authentication" represents "betrayal". For the user, adopting different strategies will bring different benefits. Their strategy choices are weighed between the convenience brought by successful authentication and being detected by the system as "betrayal", thus tightening the authentication. In the middle, a reward mechanism and a punishment mechanism are introduced. The reward mechanism means that the user "cooperates" multiple times and passes the inspection by the authentication server, thus obtaining high benefits. The punishment mechanism means that the user takes "attempt to spoof authentication" and is punished for being detected as "betrayal" by the authentication server, and finally different strategies are selected according to the game.

[0094] The Chebyshev Chaotic Map is a chaotic system based on Chebyshev polynomials, commonly used in the fields of cryptography, information security, and random number generation. Its core idea is to generate a sequence with chaotic characteristics by iterating Chebyshev polynomials, combining the determinism of mathematics and the unpredictability of chaos to achieve efficient and secure dynamic behavior. The cosine definition of the Chebyshev chaotic map is T nf(x) = cos(n·arccos(x)) mod p, where

[0095] n ∈ Z * , x ∈ (-1, +1), p is a large prime number, n is the order, and x is the Chebyshev chaotic parameter. The recurrence formula is T n (x) = (2xT n-1 (x) - T n-2 (x)) mod p. Based on the commutative property of the semigroup, the formula T m (T n (x)) = cos(m·arccos(cos(n·arccos(x)))) = cos(mn·arccos(x)) = T mn (x). Due to the intractability of its discrete logarithm, that is: given T n (x), x, and the large prime number p, it is difficult to solve for n using current algorithms within polynomial time; its Diffie - Hellman problem means that even if T n (x), T m (x), and x are known, it is difficult to solve for Tmn(x). It has characteristics 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, a private key k, and the public key is calculated as K = k * G P (X, Y). Since 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. The time complexity of the currently known optimal algorithm (such as Pollard's Rho) is O(√n), requiring exponential - level computational effort. In contrast, traditional DLP has sub - exponential time algorithms (such as the number field sieve), and there is no similar breakthrough for the discrete logarithm problem of elliptic curves (ECDLP), so ECC is difficult to be cracked within polynomial time.

[0097] Zero - Knowledge Proof (ZKP) is a cryptographic protocol that allows one party (the prover) to prove the truth of a certain statement to another party (the verifier) without revealing any specific information proving the statement. Its core lies in achieving three key characteristics: completeness (an honest prover can convince the verifier), soundness (a fraudster cannot deceive the verifier), and zero - knowledge (the verifier cannot obtain any additional information beyond the truth of the statement). For example, the prover can prove to the verifier "I know a certain secret" without revealing the secret itself, or verify the validity of a transaction without exposing the transaction details.

[0098] Homomorphic encryption allows direct computational operations to be performed on encrypted data, and the computational result after decryption is exactly the same as the result of performing the same operation on the plaintext, thus achieving the privacy protection goal of "data can be used but not seen". Its core principle is based on mathematical problems (such as the Ring Learning with Errors problem RLWE in lattice cryptography). By encrypting, the plaintext is mapped to a specific mathematical space, enabling the ciphertext to support operations such as addition and multiplication in this space. After the operations, the decrypted ciphertext is equivalent to the direct computational result of the plaintext.

[0099] In the context of autonomous driving, the user sends an authentication request to the edge server according to their trust level. The user chooses a "genuine authentication" or "impostor authentication" strategy based on the game. "Genuine authentication" means that the user submits corresponding authentication factors for authentication according to their trust level; "impostor authentication" means that the user attempts to pose as a high-level user and submits a small number of authentication factors for authentication to reduce the authentication delay.

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

[0101] In the game of these two strategies, a mixed game model and Bayesian update mechanism in game theory are adopted, combined with the statistical calculation of the user's historical behavior, to construct the following trust scoring function:

[0102]

[0103] where S t represents the current behavior trust score, L k represents the trust level divided according to the trust score, and L k takes values from 1 to 3; represents the current behavior scoring coefficient, which is also the expected revenue value at the L k level, and the specific value is obtained from the expected revenue calculation in the mixed game model; has the same value as L k and represents the number of verification factors required for different authentication levels; E max,i represents the maximum number of input errors of the i-th factor within the validity range of the timestamp, and E max,i ≤ 3; e i represents the number of input errors of the i-th factor, and 0 ≤ e i ≤ E max,i ; In descending order of k, they are 0.1, 0.15, 0.2, representing the authentication failure penalty coefficients for different authentication levels, For the recent authentication error penalty, ω is the time decay coefficient, and N last_time is the number of authentication times since the last authentication failure for this authentication.

[0104] If a user adopts the "integrity authentication strategy" for a long time, the user's authentication level will gradually increase. However, if the user adopts the "fraudulent authentication strategy" multiple times, it will inevitably be exposed in a certain detection, resulting in a reduction in the trust evaluation level and a more cumbersome authentication process. The edge server achieves defense through a probabilistic sampling detection mechanism, and performs in-depth and strict authentication on user requests with a preset probability for users of different levels, and only performs basic authentication on the user's authentication request with a probability. The expected benefits of the established hybrid game model are shown in the following table: For the expected benefits of the hybrid game model designed in this application, the expected benefits between the two entities of the authentication are shown in Table 1. Among them, x represents the probability of the user's integrity authentication;

[0105] Table 1. Benefit table of the hybrid game model

[0106]

[0107] For the hybrid game model designed in this application, the expected benefits between the two entities of the authentication are shown in Table 1. Among them, x represents the probability of the user's integrity authentication; represents the probability that the edge server performs strict authentication on users of level L k , which is set differently based on users of different levels. The probability of strict authentication for high-quality users is slightly lower, and the probability of strict authentication for risky users is high, and it is set like this; represents the time delay required for factor authentication according to level L , that is, for users of level L k , the time delay required for authenticating the authentication factors that should have been submitted; T k represents the time delay required for authentication when the user fakes the level. x

[0108] Each strategy has a corresponding expected benefit. The edge server performs strict authentication with a probability of . At this time, when the user selects the integrity authentication strategy, the expected benefit of the edge server refers to the time delay required for it to perform authentication. The expected benefit of the user is when calculating its trust score function. Among them, when the edge server performs strict authentication and detects that the user has performed integrity authentication according to its trust level, the increase in the reward for the user's trust score is large. The edge server verifies the authentication factors submitted by the user, and the time delay is the time delay required for verifying the authentication factors of this level.

[0109] The edge server performs basic authentication with a probability of . At this time, when the user selects the integrity authentication strategy, the expected benefit of the edge server refers to the time delay required for it to perform authentication. ​The time delay, and the expected benefit of the user is when calculating its trust scoring function The edge server is at Probability to perform strict authentication. At this time, when the user selects the spoofing 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 perform authentication according to its own trust level but adopts the spoofing 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 for verifying the factors submitted by the user and the authentication of the true level factors. The edge server is at Probability to perform basic authentication. At this time, when the user selects the spoofing 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 Affect 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 risky users. Classifying users, for high-trust-score users, only simple authentication is required, which greatly reduces 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 authenticate the session key and timestamp updated after the previous authentication, without additional auxiliary authentication.

[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, perform timestamp and digital certificate authentication. For users who have just completed initialization, they need to perform mutual authentication with the edge server using public and private keys and perform message authentication code verification, and then negotiate a session key for communication.

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

[0115] Among them, F is the reshaping identifier, indicating that the user has passed TA re - authentication and a new digital certificate has been issued. During the authentication process, a message authentication code is required for authentication, and information such as digital certificates and timestamps is provided.

[0116] The specific process of the protocol designed in this application refers to Figure 1 As shown, the overall network architecture of this application refers to Figure 2 As shown; thus, the specific process of each step of the protocol involved in this application is as follows:

[0117] Refer to Figure 3 As shown; 1.1: User U i , (i ∈ 1, +∞), registers through the APP in the registration center. The trusted authority center TA checks whether the user's identity exists through face biometrics and phone number. If not, it generates a user identity for the user based on the user's phone number Random number As the user's private key, and selects large prime numbers P1, P2 and the elliptic curve base point G, calculates the user's public key And issues a digital certificate for the newly registered user is the exclusive - OR operation, initializes its trust score as b, and And the registration result is returned to the user through a secure channel. TA stores the user - related information, is public information.

[0118] Refer to Figure 4 As shown; 1.2: The edge computing service registers with TA. TA generates an identity code I for the edge computing server Random number As the private key of the edge computing server, calculates the public key Chebyshev chaotic mapping code

[0119] Among them, represents as the order, as the Chebyshev chaotic mapping value with parameters, is to use the edge server identity to calculate using hash and connect it naturally with the public key, store the edge server - related information, and is sent to the edge computing server through a secure channel, is public information.

[0120] Refer to Figure 5 As shown; 1.3: The intelligent and autonomous vehicle registers with TA. TA generates Random number As the private key of intelligent and autonomous driving vehicles, allocate appropriate edge computing servers according to the operation service area of intelligent and autonomous driving vehicles, and calculate the public keys of intelligent and autonomous driving vehicles Store information related to intelligent and autonomous driving vehicles, and Send it to intelligent and autonomous driving vehicles through a secure channel It is public information

[0121] The public keys are all public, and the private keys and Chebyshev chaotic mapping values are kept confidential as private values

[0122] Refer to Figures 6-8 as shown; New user:

[0123] 2.1: When a newly registered user sends a car-hailing application to the edge server for the first time through the APP: Generate the current timestamp TS1, and use the public key of the edge computing server to encrypt the digital certificate and the timestamp TS1 to obtain the ciphertext

[0124] where ENC is the encryption method, and use the hash SHA256 to calculate the message authentication code MAC U-E =H(TS1||E U-E ), and send the timestamp TS1, the ciphertext E U-E and the message authentication code MAC U-E to the edge computing service node

[0125] 2.2: The edge server decrypts the ciphertext E U-E using its own key according to the public key calculation formula in the registration stage, and obtains where DEC is decryption. According to the probability in the hybrid game model, choose to execute the strict authentication strategy or the basic authentication strategy. If it is the strict authentication strategy, send a data request to the TA according to the obtained user digital certificate, obtain the user information stored in the TA through a secure channel, compare the user's historical authentication records and trust levels, and strictly verify whether the authentication factors are correct and complete according to the trust level; If it is the basic authentication strategy, only verify the basic legality of the authentication factors and do not perform historical behavior correlation analysis

[0126] 2.3: After obtaining the user information, first judge the validity of the timestamp where T cur1 is the current time, and perform the first factor verification; According to the timestamp in the ciphertext, calculate

[0127] Perform the second-factor verification; if it is strict authentication, at this time, strictly compare the user trust level, check whether the user has omitted to submit the authentication factor, and perform the third-factor verification. After the verification passes, generate the current timestamp TS2, encrypt it with the user's public key to obtain the ciphertext

[0128] And calculate the message authentication code MAC E-U = H(TS2||E E-U ), and send the timestamp TS2, the ciphertext E E-U and the message authentication code MAC E-U back to the user, and the user also performs the first two-factor verification.

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

[0130] And calculate the intermediate value Generate the timestamp TS3, the ciphertext and the message authentication code MAC U-E2 = H(TS3||SK||E U-E2 ), and send the timestamp TS3, the ciphertext E U-E2 and MAC U-E2 to the edge server; after receiving the ciphertext, the edge server first decrypts the ciphertext with the private key, and after verifying the validity of the timestamp, calculates the session key according to the intermediate value

[0131] Verify the message authentication code according to the calculated session key

[0132] Since then, the session key SK1 negotiation is successful.

[0133] 2.5: The edge computing server uses the calculated session key to encrypt the intermediate value and the ciphertext E U-E2 and sends it to the user to prove that it has calculated the session key. The edge computing server stores the session key SK and the user's authentication behavior during the current authentication process in the cloud storage server through a secure channel. The session key used for the subsequent user's car-hailing application is the session key SK negotiated this time.

[0134] 2.6: The edge computing server schedules the nearest idle intelligent and autonomous vehicle around the user, generates the timestamp TS4, and uses the public key of the intelligent and autonomous vehicle to encrypt the timestamp, the session key, and the user digital certificate to obtain the ciphertext Calculate the message authentication code Send the timestamp TS4, the ciphertext E E-C and the message authentication code MAC E-C to the intelligent and autonomous vehicle. The intelligent and autonomous vehicle decrypts the ciphertext using the private key, verifies the validity of the timestamp, and calculates the message authentication code using the session key and the ciphertext. Generate the timestamp TS5, encrypt it using the session key, and obtain the ciphertext Send the timestamp TS5 and the ciphertext E C-M to the edge computing server. The edge computing server decrypts the ciphertext and determines whether the intelligent and autonomous vehicle has received the session key used for communication with the user.

[0135] 2.7: Mutual authentication is performed between the user and the intelligent and autonomous vehicle using the session key SK.

[0136] 2.8: After the authentication is completed, the intelligent and autonomous vehicle sends the user authentication behavior data and TS5 to the edge server through the session key to update the user trust score and update the session key

[0137] SK new = H(SK′||TS5).

[0138] 2.9: After the authentication is completed, the user updates the session key in the background according to the timestamp TS5

[0139] SK′ new = H(SK||TS5).

[0140] Risky user: Different from new users, the difference of risky users lies in that when mutually authenticating with the edge server, the real identity information needs to be encrypted in the ciphertext wherein is the new digital certificate newly issued by TA for the risky user (that is, when the user is determined to be a risky user, a new digital certificate that requires re-application)

[0141] where F is the reshaping identifier, indicating that the user has passed the re-authentication by TA and a new digital certificate has been issued. In addition to encrypting the timestamp and digital certificate using the session key, it is also necessary to calculate the message authentication code for auxiliary authentication.

[0142] Ordinary user: Different from new users, at this time the user already has a session key and needs to perform mutual authentication with the edge server using the updated session key:

[0143] (2.1 - 2.4): The user generates the current timestamp TS7, encrypts the digital certificate and the timestamp using the session key, and obtains the ciphertext Send it to the edge server. The edge server decrypts the ciphertext using the updated session key, generates a timestamp TS8, and the timestamp, the identity identifier of the edge server Encrypt it with the updated session key and send it to the passenger for identity authentication.

[0144] High-quality user: Different from ordinary users, when authenticating, they only need to use the session key to encrypt the timestamp to calculate the ciphertext, and do not need to use digital certificates and message authentication codes for auxiliary authentication.

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

[0146] Identity identifiers of the edge server, intelligent and autonomous driving vehicles; User pseudo-anonymous digital certificate;

[0147] Private keys of the user, edge server, intelligent and autonomous driving vehicles;

[0148] Public keys of the user, edge server, intelligent and autonomous driving vehicles;

[0149] Chebyshev value of the edge server, used to calculate the session key;

[0150] H(*): Hash calculation; G p : ECC with large prime number P1 as the modulus; TS: Timestamp;

[0151] E: Ciphertext; MAC: Message authentication code; T cen Intermediate value for calculating the session key.

[0152] In some embodiments of the present application, the present application further provides a multi-level user anonymous security authentication system based on a game theory trust evaluation mechanism, using the above-mentioned multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, including:

[0153] Ciphertext generation module, used to generate matching user information according to the car-hailing application of the registered user terminal and encrypt the user information with the public key of the registered edge computing server to generate a user ciphertext;

[0154] Information acquisition module, used to decrypt the user ciphertext through the edge server key to obtain user information;

[0155] Verification processing module, used to complete two-factor authentication by verifying the validity of the timestamp and negotiate a session key, and then store the session key in the cloud storage server and use it as the session key for the subsequent car-hailing application of the user terminal;

[0156] A vehicle processing module, configured to dispatch the nearest idle 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.

[0157] A communication module, configured to perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using the session key, and update the user trust score and the session key after authentication to perform subsequent communication using the session key.

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

[0159] In some embodiments of the present application, the present application also relates to a computer, including the above-mentioned computer storage medium.

[0160] In the description of this specification, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

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

Claims

1. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism, characterized in that, It includes the following steps: S1: Generate matching user information according to the car-hailing application of the registered user terminal, and encrypt the user information with the public key of the registered edge computing server to generate user ciphertext; S2: Decrypt the user ciphertext with 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 subsequent car-hailing applications of the user terminal; S4: Dispatch the nearest idle registered intelligent and autonomous vehicle around the passenger terminal and encrypt the session key and user information with the public key of the intelligent and autonomous vehicle; S5: Perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using the session key, and update the user trust score and session key after authentication to use the session key for subsequent communication.

2. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 1, characterized in that When the user terminal registers with the registration center, the method includes: S101: When the trusted authority center TA determines that the user terminal identity does not exist through face biometric recognition and phone number check, generate a user identity for the user terminal based on the phone number of the user terminal and use the random number as the user's private key; S102: Select large prime numbers P1, P2 and the elliptic curve base point G and calculate the public key of the user terminal Among them, is the ECC with the large prime number P1 as the modulus; S103: Issue a digital certificate to the newly registered user terminal where H is hash calculation, is exclusive OR operation, and its trust score is initialized to b; then and the registration result are returned to the user terminal through a secure channel, and the TA stores the information related to the user terminal, which is public information.

3. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 2, characterized in that When the edge computing server registers with the registration center, the method includes: S111: The trusted authority center TA generates an identity code for the edge computing server and uses the random number as the private key of the edge computing server; S112: Calculate the public key of the edge computing server S113: Calculate the Chebyshev chaotic mapping code of the edge computing server Among them, represents the Chebyshev chaotic mapping value with as the order and as the parameter, that is, the identity of the edge server is calculated using hashing and naturally concatenated with the public key; S114: Store the information related to the edge server and send it to the edge computing server via a secure channel, which is public information.

4. A multi - level user anonymous security authentication method based on a game - theory trust evaluation mechanism according to claim 3, characterized in that, When the intelligent and autonomous vehicle registers with the registration center, the method includes: S115: The trusted authority center TA generates an identity code for the intelligent and autonomous vehicle and uses the random number as the private key of the intelligent and autonomous vehicle; S116: Allocate a matching edge computing server according to the operation service area of the intelligent and autonomous vehicle; S117: Calculate the public key of computational intelligence and autonomous vehicles S118: Store information related to intelligent and autonomous vehicles and send it to the intelligent and autonomous vehicles via a secure channel, which is public information.

5. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 1 or 4, characterized in that In step S1, the method includes: S121: Generate the current timestamp TS1 according to the first car-hailing application sent by the registered user terminal to the edge computing server; S122: Encrypt the digital certificate and timestamp TS1 with the public key of the edge computing server to obtain the user ciphertext and calculate the message authentication code MAC using the hash SHA256 U-E = H(TS1 || E U-E ), where ENC is the encryption method; S123: Send the timestamp TS1, the ciphertext E U-E and the message authentication code MAC U-E to the edge computing service node.

6. The multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 5, characterized in that, In step S2, the method includes: S201: Decrypt the user ciphertext with the edge server key according to the public key calculation formula of the edge server in the registration phase to obtain where DEC stands for decryption; S202: Select whether to execute the strict authentication policy or the basic authentication policy according to the probability in the hybrid game model. If it is the strict authentication policy, send a data request to the TA according to the obtained user digital certificate, obtain the user information stored in the TA through the secure channel, compare the user's historical authentication records and trust levels, and strictly verify whether the authentication factors are correct and complete according to the trust level; if it is the basic authentication policy, only verify the basic legality of the authentication factors and do not perform historical behavior correlation analysis.

7. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 6, characterized in that In step S3, the method further includes: S301: After obtaining user information, determine the validity of the timestamp Perform the first factor verification; where T cur1 is the current time, and ΔT is the valid time interval; S302: Calculate according to the timestamp TS1 in the user ciphertext E U-E for secondary factor verification; if it is strict authentication, strictly compare the user trust level at this time, check whether the user has omitted to submit authentication factors, and conduct tertiary factor verification; C U-E ​ S303: After verification, generate the current timestamp TS2 and encrypt it with the public key of the user terminal to obtain the user ciphertext and calculate the message authentication code MAC E-U = H(TS2||E E-U ); S304: Send the timestamp TS2, the user ciphertext E E-U and the message authentication code MAC E-U back to the user terminal, and the user terminal also performs the first two-factor verification; S305: After the user terminal successfully performs two-factor authentication, the user terminal uses the Chebyshev chaotic mapping value of the edge computing server as a parameter and the user terminal private key as the order, and uses the large prime number P2 to calculate the session key. And calculate the intermediate value S306: Generate timestamp TS3 and ciphertext along with message authentication code MAC U-E2 = H(TS3||SK||E U-E2 ), and send timestamp TS3, ciphertext E U-E2 and MAC U-E2 to the edge server; S307: The edge server decrypts the ciphertext E with the private key of the user terminal. After verifying the validity of the timestamp, it calculates the session key according to the intermediate value U-E2 and verifies the message authentication code MA according to the session key SK′ to complete the negotiation of the session key SK; ​ S308: The edge computing server uses the calculated session key to encrypt the intermediate value and the ciphertext E U-E2 and sends them to the user to prove to the user that it has 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 the secure channel, and uses the session key SK as the session key for subsequent car-hailing applications of the user terminal.

8. A multi - level user anonymous security authentication method based on a game - theory trust evaluation mechanism according to claim 7, characterized in that, In step S4, the method includes: S401: The edge computing server dispatches the nearest idle intelligent and autonomous vehicle around the user terminal and generates a timestamp TS4; S402: Use the public key of the intelligent and autonomous vehicle to encrypt the timestamp TS4, the session key SK, and the user digital certificate to obtain the ciphertext S403: Calculate the message authentication code Furthermore, the timestamp TS4, the ciphertext E E-C and the message authentication code MAC E-C are sent to the intelligent and autonomous vehicle; S404: The intelligent and autonomous vehicle decrypts the ciphertext E using the private key, verifies the validity of the timestamp, and calculates the message authentication code MAC using the session key SK and the ciphertext E E-C ; E-C ; E-c ; S405: Generate a timestamp TS5, encrypt it with the session key SK to obtain the ciphertext and send the timestamp TS5 and the ciphertext E C-M to the edge computing server; S406: The edge computing server decrypts the ciphertext E C-M and decrypts it.

9. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 8, characterized in that In step S5, the method includes: S501: Perform mutual authentication between the user terminal and the intelligent and autonomous vehicle using the session key SK; S502: The intelligent and autonomous vehicle sends the user authentication behavior data and TS5 to the edge server through the session key to update the user trust score and update the session key SK new = H(sK′||TS5); S503: The user updates the session key SK' according to the timestamp TS5 in the background new = H(SK || TS5).

10. A multi-level user anonymous security authentication method based on a game theory trust evaluation mechanism according to claim 9, characterized in that The method further includes: Divide users into risky users, ordinary users, and high-quality users; Risk users are different from new users. When risk users authenticate with each other on the edge server, they need to encrypt their real identity information in the ciphertext wherein, is the new digital certificate newly issued by TA for risk users, that is, when a user is determined to be a risk user, a new digital certificate is required to be re-applied Where F is the reshaping identifier, indicating that the user has been re-authenticated by TA and a new digital certificate has been issued. In addition to encrypting the timestamp and digital certificate using the session key, it is also necessary to calculate the message authentication code for auxiliary authentication; Ordinary users are different from new users. At this time, the user already has a session key and needs to use the updated session key to authenticate with the edge server: The user generates the current timestamp TS7, encrypts the digital certificate and the timestamp using the session key to obtain the ciphertext and sends it to the edge server. The edge server decrypts the ciphertext using the updated session key, generates the timestamp TS8, and sends the ciphertext timestamp TS8 and the identity identifier of the edge server encrypted with the updated session key to the ordinary user for identity authentication; High-quality users are different from ordinary users. When authenticating, they only need to use the session key to encrypt the timestamp to calculate the ciphertext, and do not need to use digital certificates and message authentication codes for auxiliary authentication.

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