Power distribution network data asset identity authentication method based on zero knowledge proof

Abstract

The invention discloses a zero knowledge proof-based power distribution network data asset identity authentication method, which comprises equipment, a proof module and a server, and comprises the following steps: a system deployment stage: a server S generates some parameters for a system, the S selects a large prime number P, and then expands to Chebyshev polynomial chaotic mapping and an anti-collision hash function, finally, the S issues a common parameter CS; in the device registration stage, the device D registers on the S and obtains the voucher through the secure channel; and a login authentication and key negotiation stage: the S receives a login request message from the D, after mutual authentication is successfully completed, the U and the D establish a secure session key K, and the key is used for future secure communication between the U and the D. According to the invention, an efficient and safe identity authentication mechanism is realized on the premise of ensuring that sensitive information of the server and the equipment is not leaked; the identity authenticity of the equipment and the legality of the access authority can be ensured, and various potential network threats and attacks can be effectively resisted.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution networks, and in particular to a method for authenticating data assets of power distribution networks based on zero-knowledge proof. Background Art

[0002] Due to the reproducibility of digital information, the identity authentication of network entities has become a challenging problem. The identity authentication system mainly includes network entities such as provers, verifiers, trusted third parties and attackers. The prover proves his identity to the verifier through various means, the verifier takes corresponding measures to verify the prover's identity, the trusted third party assists the prover and verifier to complete the identity authentication process, and the attacker attacks the identity authentication process through various means.

[0003] In the field of cyberspace security, remote identity authentication occupies a core position. In this process, the prover and the verifier are usually distributed in different locations and rely on the Internet for information exchange. Their main task is to confirm each other's true identity through a series of complex operations or encryption algorithms to ensure the authenticity and credibility of both parties in communication. The core goal of remote identity authentication is to prevent attackers from impersonating any party to participate in communication, thereby protecting both parties in communication from potential security threats and economic losses. This mechanism is crucial in the network environment and plays an irreplaceable role in ensuring data security and business continuity. Identity authentication is one of the key mechanisms to ensure cyberspace security. Existing identity authentication schemes are particularly vulnerable to internal privilege attacks and network management node data leakage disguise attacks. From a security perspective, most current authentication schemes have significant deficiencies in resisting internal privilege attacks. Once internal personnel illegally obtain the key issued to the device, they can easily impersonate a legitimate device to pass the authentication, which seriously threatens the security of the system. Similarly, the risk of server data leakage cannot be ignored, because most authentication information is stored in the database or generated based on database data. Once data leakage occurs, the reliability and effectiveness of the entire identity authentication scheme will be greatly challenged. Therefore, we urgently need to develop more robust and secure authentication schemes to defend against these potential threats.

[0004] In the smart grid environment, in order to ensure that devices can safely and legally access the data assets of the distribution network, the current verification process for device identity and permissions is relatively simple and can be easily circumvented or bypassed by existing technical means. Therefore, it is urgent to introduce a more rigorous and efficient identity authentication mechanism to strengthen the security protection of the system and prevent illegal or unauthorized devices from accessing and obtaining sensitive information.

[0005] In the complex network environment of smart grids, current device authentication mechanisms usually rely on devices to provide personal information for verification, which poses certain security risks to both devices in the network and clients of the distribution network. In order to improve system security, we urgently need an authentication scheme that does not need to expose device specific information, thereby avoiding potential privacy leaks and data security risks. This new authentication method should be able to achieve efficient and reliable device authentication without relying on detailed device information.

[0006] Zero-knowledge proof is a method of proving that a statement is correct without revealing key information. Zero-knowledge proof is a cryptographic protocol proposed by Goldwasser et al. in 1989. In the zero-knowledge proof system, the main roles include the prover and the verifier. The prover generates a proof based on a statement and does not reveal sensitive information to the verifier.

[0007] Let P be the prover and V be the verifier. Then a zero-knowledge proof system must satisfy at least the following properties:

[0008] (1) Correctness: P cannot deceive V, that is, if P does not know a certain proof method or evidence, V will have a low probability of believing that P can prove something.

[0009] (2) Completeness: V cannot deceive P, that is, if P learns a certain proof method or evidence, then P can make V believe with an absolute advantage that he can prove something.

[0010] (3) Zero-knowledge: V can verify whether the proof given by P is reliable, but cannot obtain any additional information from P's proof.

[0011] Conditional proof is the most commonly used zero-knowledge proof application attribute, which allows the prover to prove to the verifier that the data satisfies a certain equality constraint or model without leaking any additional information. Some researchers have applied this function to the field of power grid dispatching to verify the reliability of dispatching instructions. For example, some literature uses conditional proof to verify that dispatching instructions satisfy the optimal control model of the power grid, that is, taking the dispatch value as the decision variable, proving that the decision variable satisfies the gradient-based optimal control equation constraint, and ensuring the security of the underlying computing information of the dispatching agency, in this way, the generator set can first verify the instruction evidence and then choose whether to accept the dispatching instruction. At the same time, conditional proof can be combined with data metering to achieve accurate meter reading without obtaining user private information; some literature considers that the meter time series load data will leak the user's living habits, and designs a post-meter electricity fee calculation method based on conditional proof. In the context of the power sales company not supervising the user's load data, the accurate metering of electricity fees is achieved. After the user receives the electricity price information from the power sales company, the electricity fee is calculated according to the electricity price information after the meter. At the same time, it is necessary to form evidence to prove that the electricity fee calculation result satisfies the pricing equation model of the power sales company. Therefore, the user only needs to submit the electricity fee calculation result and calculation evidence to the power sales company to avoid the leakage of load data. Conditional proof can also be combined with identity authentication. The prover generates evidence to prove his identity by solving a specific secret function. In the electric vehicle charging reservation, the electric vehicle needs to authenticate the identity of the charging service, which may cause the exposure of the connection between identity information and charging mode. Therefore, some literature applies zero-knowledge proof to the pseudonym mechanism of electric vehicles. First, the charging station creates a model based on a secret function and passes it to the electric vehicle to be charged. The electric vehicle needs to provide a solution that satisfies the secret function model and give evidence. Once the evidence is verified, proving that the electric vehicle knows the secret function sent by the service provider, the charging station will send a random pseudonym to the electric vehicle and bind it to the charging service. The electric vehicle uses the charging service through the pseudonym, and the entire process is anonymous to avoid the connection between the charging mode and identity information. Summary of the invention

[0012] The purpose of the present invention is to solve the shortcomings existing in the prior art, and to propose a distribution network data asset identity authentication method based on zero-knowledge proof, which is used in the distribution network server environment. The server remotely authenticates the device without any transmission or storage of any sensitive information from the device, such as passwords, parameter characteristics, etc.; the server and the device complete the authentication and key negotiation stages without leaking any sensitive information.

[0013] In order to achieve the above object, the present invention adopts the following technical solutions:

[0014] The distribution network data asset identity authentication method based on zero-knowledge proof includes a device, a proof module and a server, and specifically includes the following steps:

[0015] S1: System deployment phase: In this phase, server S generates some parameters for the system. Server S selects a large prime number P and then expands to the Chebyshev polynomial chaotic map T n (x)mod(p), collision-resistant hash function H 1 (·):{0,1} * →Z p * ,H 2 (·):{0,1} * →{0,1} l , finally the server S publishes the public parameter CS;

[0016] S2: Device registration phase:

[0017] S2a: Device D selects its registration ID, password PW, and enters parameter characteristics Par on the device;

[0018] S2b: Device extraction: fuzzy extraction of parameter features of device D (θ i ,σ i )=Gen(Par) and generate random numbers, then calculate H 1 and H 2 , let T be the time function, the return value is the registration timestamp if the time is within a certain time period, and T is 0 if it exceeds this time period;

[0019] S2c: Proof module generates T xi (X i ) and the relevant parameters (T xi (X i ),ID) is sent to server S through a secure channel;

[0020] S2d: Server S receives the registration information and calculates M = T xs (X i ), then S will <m>Return to the device and send IDT xi (X i ),X i Stored in a database;

[0021] S2e: After receiving the message M from the server S, the device stores M and T on the device;

[0022] S3: Login authentication and key negotiation phase:

[0023] S3a: Device U starts to log in and access the device, enters the registered identity ID, password, and parameter feature information Par, and the device uses auxiliary parameters and fuzzy extractor to obtain fuzzy extraction feature information θ i =Gen(Par), and calculate x i =H 1 and X i =H 2 ;

[0024] S3b: The device generates a timestamp T s1 , choose two random numbers p a ,e a ∈Z p * , and calculate TID=ID⊕H 2 (T pa (M)||T s1 ),PA=T pa (X i ),N i =e a ⊕X i ⊕T s1 ⊕PA, then M= <TID,T s1 ,PA,N i >Send to remote server S;

[0025] S3c: After receiving the information from the device, the server S immediately generates a timestamp T * s1 And verify

[0026] |T * s1 -T s1 | Is it less than or equal to ΔT? If it passes, the server S calculates ID = H 2 ⊕TID and look it up from the database <ID,T xi (X i ),X i > At the same time, verify whether the device certificate has expired. If it has expired, terminate this stage and reply to the device that the certificate has expired. Otherwise, S generates a timestamp T * s2 , and select two random numbers p s ,e s , solve for e a =N i ⊕T s1 ⊕X i ⊕PA,PS=T ps (X i ),ω s =p s +x s e a , K is =H 2 , Nj=X i ⊕e s ⊕T * s2 , and finally M 2 = <Kis⊕PS||ω s ,Nj,T * s2 >Send to the device;

[0027] S3d: The device generates a timestamp T immediately after receiving it s2 , verify |T * s2 -T s2 | Is it less than or equal to ΔT? If it passes, solve e s To obtain ω and T ps , then the device verifies the identity of the server S and calculates ω a =pa+x i e s and SK=H 2 , and finally the device generates a timestamp T s3 And M 3 =<ω a ⊕K * is ⊕T s3 ⊕T s3 >Send to server S and store SK as session key;

[0028] S3e: Server S receives information M 3 Generate a timestamp T immediately after * s3 , verify that it is less than the maximum transmission delay and M 3 After containing relevant information, if it fails, this stage will be terminated directly, otherwise the server S recognizes the device identity and calculates SK * as a session key;

[0029] S3f: Server S assigns device D the permission to read the device-related distribution network data assets.

[0030] As a further technical solution of the present invention, the device refers to the power distribution equipment in the distribution network, such as intelligent switches, substation identification equipment, etc.

[0031] As a further technical solution of the present invention, the proof module has a certain computing capability for processing information such as identity, password, and parameter characteristics submitted by the device to meet the computing needs of the zero-knowledge proof process.

[0032] As a further technical solution of the present invention, the server acts as a verifier in the identity authentication process and verifies the credentials and calculation results submitted by the device.

[0033] As a further technical solution of the present invention, in S1, for the convenience of description, when calculating a single Chebyshev polynomial, T n (x) represents T n (x)mod(p).

[0034] As a further technical solution of the present invention, in S1, H in the collision-resistant hash function 2 The result of (·) can be converted to a non-negative integer through binary, and l is the hash function H 2 The length of the result.

[0035] As a further technical solution of the present invention, in S2, during the device registration phase, the device D registers on the server S and obtains credentials through a secure channel.

[0036] As a further technical solution of the present invention, in S3, during the login authentication and key negotiation phase, the server S receives a login request message from the device D. After successfully completing mutual authentication, U and D establish a secure session key K, which will be used for future secure communications between them.

[0037] As a further technical solution of the present invention, in S3c and S3d, ΔT is the maximum transmission delay.

[0038] The beneficial effects of the present invention are:

[0039] 1. An efficient and secure identity authentication mechanism is implemented under the premise of ensuring that sensitive information of servers and devices is not leaked; through zero-knowledge proof technology, we can verify the identity of users without directly transmitting or verifying any actual data, thereby greatly improving the security and privacy protection capabilities of data assets.

[0040] 2. Instead of relying on traditional single authentication methods, such as passwords or biometrics, multiple verification factors are combined, such as device ID, password, device fingerprint and other parameters, to build a more rigorous and secure authentication system; through this advanced authentication method, we can ensure the authenticity of the device's identity and the legitimacy of access rights, and effectively resist various potential network threats and attacks. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is an identity authentication diagram based on zero-knowledge proof for the distribution network data asset identity authentication method based on zero-knowledge proof proposed in the present invention. DETAILED DESCRIPTION

[0042] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0043] Please refer to the attached Figure 1 , a distribution network data asset identity authentication method based on zero-knowledge proof, including equipment, proof module and server, equipment refers to distribution equipment in the distribution network, such as intelligent switches, substation identification equipment, etc., the proof module has a certain computing power, which is used to process the identity, password and parameter characteristics submitted by the equipment to meet the computing needs of the zero-knowledge proof process, and the server, as the verifier in the identity authentication process, verifies the credentials and calculation results submitted by the equipment;

[0044] The specific steps include:

[0045] S1: System deployment phase: In this phase, server S generates some parameters for the system. Server S selects a large prime number P and then expands to the Chebyshev polynomial chaotic map T n (x)mod(p), for the convenience of description, when calculating a single Chebyshev polynomial, T n (x) represents T n (x)mod(p), collision-resistant hash function H 1 (·):{0,1} * →Z p * ,H 2 (·):{0,1} * →{0,1} l , where H 2 The result of (-) can be converted to a non-negative integer by binary, and l is the hash function H 2 The length of the result, and finally the server S publishes the public parameter CS;

[0046] S2: Device registration phase: In this phase, device D registers on server S and obtains credentials through a secure channel;

[0047] S2a: Device D selects its registration ID, password PW, and enters parameter characteristics Par on the device;

[0048] S2b: Device extraction: fuzzy extraction of parameter features of device D (θ i ,σ i )=Gen(Par) and generate random numbers, then calculate H 1 and H 2 , let T be the time function, the return value is the registration timestamp if the time is within a certain time period, and T is 0 if it exceeds this time period;

[0049] S2c: Proof module generates T xi (X i ) and the relevant parameters (T xi (X i ),ID) is sent to server S through a secure channel;

[0050] S2d: Server S receives the registration information and calculates M = T xs (X i ), then S will <m>Return to the device and send IDT xi (X i ),X i Stored in a database;

[0051] S2e: After receiving the message M from the server S, the device stores M and T on the device;

[0052] S3: Login authentication and key agreement phase: In this phase, the server S receives a login request message from the device D. After successfully completing mutual authentication, U and D establish a secure session key K, which will be used for future secure communications between them.

[0053] S3a: Device U starts to log in and access the device, enters the registered identity ID, password, and parameter feature information Par, and the device uses auxiliary parameters and fuzzy extractor to obtain fuzzy extraction feature information θ i =Gen(Par), and calculate x i =H 1 and X i =H 2 ;

[0054] S3b: The device generates a timestamp T s1 , choose two random numbers p a ,e a ∈Z p * , and calculate TID=ID⊕H 2 (T pa (M)||T s1 ),PA=T pa (X i ),N i =e a ⊕X i ⊕T s1 ⊕PA, then M= <TID,T s1 ,PA,N i >Send to remote server S;

[0055] S3c: After receiving the information from the device, the server S immediately generates a timestamp T * s1 And verify

[0056] |T * s1 -T s1 | is less than or equal to ΔT, where ΔT is the maximum transmission delay. If it passes, the server S calculates ID = H 2 ⊕TID and look it up from the database <ID,T xi (X i ),X i > At the same time, verify whether the device certificate has expired. If it has expired, terminate this stage and reply to the device that the certificate has expired. Otherwise, S generates a timestamp T * s2 , and select two random numbers p s ,e s , solve for e a =N i ⊕T s1 ⊕X i ⊕PA,PS=T ps (X i ),ω s =p s +x s e a , K is =H 2 , Nj=X i ⊕e s ⊕T * s2 , and finally M 2 = <Kis⊕PS||ω s ,Nj,T * s2 >Send to the device;

[0057] S3d: The device generates a timestamp T immediately after receiving it s2 , verify |T * s2 -T s2 | Is it less than or equal to ΔT, where ΔT is the maximum transmission delay. If it passes, solve e s To obtain ω and T ps , then the device verifies the identity of the server S and calculates ω a =pa+x i e s and SK=H 2 , and finally the device generates a timestamp T s3 And M 3 =<ω a ⊕K * is ⊕T s3 ⊕T s3 >Send to server S and store SK as session key;

[0058] S3e: Server S receives information M 3 Generate a timestamp T immediately after * s3 , verify that it is less than the maximum transmission delay and M 3 After containing relevant information, if it fails, this stage will be terminated directly, otherwise the server S recognizes the device identity and calculates SK * as a session key;

[0059] S3f: Server S assigns device D the permission to read the device-related distribution network data assets.

[0060] From the above description, it can be seen that the above-mentioned embodiments of the present invention achieve the following technical effects: under the premise of ensuring that sensitive information of the server and the device is not leaked, an efficient and secure identity authentication mechanism is implemented; through zero-knowledge proof technology, we can verify the identity of the user without directly transmitting or verifying any actual data, thereby greatly improving the security and privacy protection capabilities of data assets.

[0061] Instead of relying on traditional single authentication methods, such as passwords or biometrics, we combine multiple verification factors, such as device ID, password, device fingerprint and other parameters, to build a more rigorous and secure authentication system. Through this advanced authentication method, we can ensure the authenticity of the device's identity and the legitimacy of access rights, and effectively resist various potential network threats and attacks.

[0062] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present invention (including the claims) is limited to these examples. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity.

[0063] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.< / m> < / m>

Claims

1. A distribution network data asset identity authentication method based on zero-knowledge proof, characterized in that: The device includes a device, a certification module and a server, and specifically includes the following steps: S1: System deployment phase: In this phase, server S generates some parameters for the system. Server S selects a large prime number P and then expands to the Chebyshev polynomial chaotic map T n (x) mod (p), collision-resistant hash function H1(·): {0,1} * →Z p * ,H2(·):{0,1} * →{0,1} l , finally the server S publishes the public parameter CS; S2: Device registration phase: S2a: Device D selects its registration ID, password PW, and enters parameter characteristics Par on the device; S2b: Device extraction: fuzzy extraction of parameter features of device D (θ i ,σ i )=Gen(Par) and generate random numbers, then calculate H1 and H2, let T be the time function, the return value is the registration timestamp if the time is within a certain time period, and T is 0 if it exceeds this time period; S2c: Proof module generates T xi (X i ) and the relevant parameters (T xi (X i ),ID) is sent to the server S through a secure channel; S2d: Server S receives the registration information and calculates M = T xs (X i ), then S will <m>Return to the device and set ID T xi (X i ),X i Stored in a database;< / m> S2e: After receiving the message M from the server S, the device stores M and T on the device; S3: Login authentication and key negotiation phase: S3a: Device U starts to log in and access the device, enters the registered identity ID, password, and parameter feature information Par, and the device uses auxiliary parameters and fuzzy extractor to obtain fuzzy extraction feature information θ i =Gen(Par), and calculate x i =H1 and X i =H2; S3b: The device generates a timestamp T s1 , choose two random numbers p a ,e a ∈Z p * , and calculate Then M= <TID,T s1 ,PA,N i >Send to remote server S; S3c: After receiving the information from the device, the server S immediately generates a timestamp T * s1 And verify |T * s1 -T s1 | is less than or equal to ΔT? If yes, server S calculates And search from the database <ID,T xi (X i ),X i > At the same time, verify whether the device certificate has expired. If it has expired, terminate this stage and reply to the device that the certificate has expired. Otherwise, S generates a timestamp T * s2 , and select two random numbers p s ,e s , solve PS=T ps (X i ),ω s =p s +x s e a , Finally Send to the device; S3d: The device generates a timestamp T immediately after receiving it s2 , verify |T * s2 -T s2 | Is it less than or equal to ΔT? If it passes, solve e s To obtain ω and T ps , then the device verifies the identity of the server S and calculates ω a =pa+x i e s And SK = H2, the device generates a timestamp T s3 and will Send to server S and store SK as session key; S3e: Server S generates a timestamp T immediately after receiving information M3 * s3 , after verifying that it is less than the maximum transmission delay and M3 contains relevant information, if it fails, this stage is terminated directly, otherwise the server S recognizes the device identity and calculates SK * as a session key; S3f: Server S assigns device D the permission to read the device-related distribution network data assets.

2. The method for authenticating distribution network data assets based on zero-knowledge proof according to claim 1, characterized in that: The equipment mentioned above refers to the power distribution equipment in the power distribution network, such as smart switches, substation identification equipment, etc.

3. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 2 is characterized in that: The proof module has a certain computing capability and is used to process information such as identity, password, and parameter characteristics submitted by the device to meet the computing needs of the zero-knowledge proof process.

4. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 3 is characterized in that: The server acts as a verifier in the identity authentication process and verifies the credentials and calculation results submitted by the device.

5. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 1, characterized in that: In S1, for the convenience of description, when calculating a single Chebyshev polynomial, T n (x) represents T n (x)mod(p).

6. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 5, characterized in that: In S1, the result of H2(-) in the collision-resistant hash function can be converted into a non-negative integer by binary conversion, and l is the length of the result of the hash function H2.

7. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 1, characterized in that: In S2, during the device registration phase, device D registers on server S and obtains credentials through a secure channel.

8. The method for authenticating distribution network data assets based on zero-knowledge proof according to claim 1, characterized in that: In S3, during the login authentication and key negotiation phase, the server S receives a login request message from the device D. After successfully completing mutual authentication, U and D establish a secure session key K, which will be used for future secure communications between them.

9. The method for authenticating the data asset of a distribution network based on zero-knowledge proof according to claim 1, characterized in that: In S3c and S3d, ΔT is the maximum transmission delay.

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