Blockchain storage and self-evidence auditing method for mixed authentication behavior of trusted data space

Abstract

The application discloses a kind of blockchain storage and self-evidence audit method of mixed authentication behavior of trusted data space, and the initial state value of each business dimension is respectively assigned to the corresponding independent generation element base by configuring initialization parameter to accumulator execution engine;Authentication gateway extracts the key event sequence of heterogeneous dimension and sends to engine;The current event feature is cascaded mapped into entangled prime number using state entanglement mechanism with the state value of the dimension at the last time, and the parameter dependence of the current behavior on the historical trajectory is established;The recursive evolution of dimension state is executed by modular exponentiation operation, and the algebraic locking of strict time sequence dependence relationship of authentication behavior is realized using the nesting characteristics of power operation;Synthesize the global trajectory characteristic value of fixed length and execute blockchain storage when authentication process ends.The application realizes the time sequence locking and privacy audit of mixed authentication trajectory.

Description

Technical Field

[0001] This invention relates to the fields of data security and blockchain technology, specifically to a blockchain-based method for evidence storage and self-certification auditing of trusted data space hybrid authentication behavior. Background Technology

[0002] With the development of the digital economy, trusted data spaces have been widely deployed as computing environments that promote the secure flow of cross-domain data. In trusted data spaces, systems typically use hybrid authentication mechanisms to verify data access requests in multiple dimensions, including identity attribute verification, access control policy evaluation, and data flow rule checks. In order to meet data compliance and security supervision requirements, business systems need to retain evidence and audit various authentication behaviors during the data interaction process to ensure the security and controllability of the data flow chain.

[0003] In most existing business systems, the evidence storage and auditing of hybrid authentication behaviors usually rely on early simple log recording and traditional one-way hash chain technology. Specifically, the system collects independent operation logs at each node of the authentication process, calculates the hash digest of the log data of each node separately, and submits them to the blockchain network for solidification and storage in the order of the physical time of the events. When a compliance review is required, the auditor will extract the historical digest records from the blockchain and compare them one by one with the plaintext log files provided by the evidence storage party to verify whether each independent authentication step actually occurred.

[0004] However, existing evidence storage mechanisms cannot effectively guarantee the unforgeability of temporal causal logic in hybrid authentication processes. Since the log data generated by each authentication step is treated as independent static records and uploaded to the blockchain separately, the evidence storage data of the current step does not inherit the cumulative state characteristics of the previous operation in terms of mathematical structure. This evidence storage method, which separates data from temporal sequence, results in a lack of endogenous algebraic binding relationship between discrete authentication events. When the system is maliciously tampered with, causing the actual execution order of hybrid authentication to be replaced, or when the records of intermediate steps are partially forged, traditional discrete digest comparison methods are unable to directly identify the destruction of strict temporal dependencies at the underlying mathematical level. This makes it impossible for existing auditing methods to provide compliance proofs with strong time dependence and determinism for the entire hybrid authentication flow. Summary of the Invention

[0005] This invention discloses a blockchain-based method for storing and auditing trusted data space hybrid authentication behavior, which relates to the fields of data security and blockchain storage technology. It mainly addresses the technical shortcomings of existing technologies in the process of storing hybrid authentication trajectories, which makes it difficult to simultaneously consider temporal causal locking and multi-dimensional privacy auditing.

[0006] The first aspect of this invention provides a blockchain-based method for evidence storage and self-verification auditing of hybrid authentication behaviors in trusted data spaces, comprising:

[0007] The accumulator execution engine performs system initialization, selects two large prime numbers and calculates their product as the modulus, and determines multiple generator bases that satisfy algebraic independence within the loop group defined by the modulus operation. The generator bases correspond to the authentication method dimension, data tag dimension, and contract execution behavior dimension, respectively, and the initial state values ​​of each business dimension are assigned to the corresponding independent generator bases.

[0008] The authentication gateway performs protocol parsing on the access request, extracts key event sequences belonging to different business dimensions, and sends the key event sequences to the accumulator execution engine;

[0009] The accumulator execution engine performs a prime number mapping operation based on state entanglement, concatenating the currently captured key event with the state value of the corresponding business dimension at the previous moment, and calling the prime number mapping function to map the concatenation result to entangled prime numbers, so as to establish the parameter dependence of the current behavior on the historical trajectory.

[0010] The accumulator execution engine performs a recursive evolution of the execution dimension state, using the entangled prime number as an exponent to perform a modular exponentiation operation on the previous state value of the corresponding business dimension, and updates the current state value.

[0011] At the end of the hybrid authentication process, the accumulator execution engine obtains the final state components of each business dimension at the end time, performs multiplication operations using the corresponding generator basis, and synthesizes global trajectory feature values.

[0012] The authentication gateway receives the global trajectory feature value and encapsulates it with business metadata into a notarized transaction, which is then submitted to the blockchain network.

[0013] After the blockchain node performs consensus verification, it persistently stores the evidence data containing the global trajectory feature value in the block;

[0014] In response to the audit request, the evidence storage party calculates the dimensional component witness value and the blinding factor and sends them to the audit node. The audit node retrieves the solidified global trajectory feature value from the blockchain and performs an algebraic equation comparison to determine the compliance of the authentication trajectory.

[0015] A second aspect of this invention provides a blockchain-based evidence storage and self-certification auditing system for trusted data space hybrid authentication behavior, comprising:

[0016] The authentication requester is used to initiate access requests for controlled resources within a trusted data space;

[0017] The authentication gateway is used to monitor the authentication flow and extract key events from heterogeneous dimensions, as well as to perform evidence storage transaction encapsulation and evidence storage notification.

[0018] The accumulator execution engine is used to perform initialization configuration, state entanglement mapping, state recursive accumulation, and eigenvalue homomorphic synthesis.

[0019] Blockchain nodes are used to perform consensus verification and distributed persistent storage for evidence-based transactions.

[0020] Audit nodes are used to perform algebraic verification on blockchain-based solidified data using witness data.

[0021] The present invention, by adopting the above technical solution, can bring the following beneficial effects:

[0022] 1. This invention concatenates the feature vector of the current authentication event with the dimensional state components of the previous time step and maps them to entangled prime numbers. Since each prime number generated contains the accumulated fingerprint information of all previous historical operations at the algebraic level, it establishes a strong parameter dependence of the current behavior on the historical trajectory. When the authentication steps are logically reversed or the content is tampered with, the final algebraic verification will fail with a high probability in the modulus space. Forging a legitimate verification value is computationally infeasible. This invention achieves a high-strength lock for the strict execution order of mixed authentication behaviors by using an algebraic binding mechanism.

[0023] 2. This invention assigns generators that satisfy algebraic independence to each other as algebraic independent basis for multidimensional business during the initialization phase, and uses modular multiplication to construct blinding factors containing trajectory features of non-target dimensions during the audit verification phase. Audit nodes only need to obtain the witness value of the target dimension to reconstruct the verification equation without touching the plaintext attributes of other dimensions. This solves the privacy leakage problem that exists when audit nodes perform compliance checks on specific business elements in complex hybrid authentication environments, and realizes dimensional isolation audit without exposing background data.

[0024] 3. This invention utilizes the homomorphic properties of modular exponentiation to recursively accumulate the states of discrete key events, compressing multi-dimensional hybrid authentication behaviors into a fixed-length global trajectory feature value whose length is determined by the modulus width of the secure computation space. Since the physical length of this feature value does not change with the increase of authentication flow steps or the expansion of business scale, it effectively reduces the storage load and network communication overhead of blockchain nodes when persistently storing massive amounts of authentication evidence, and achieves efficient storage and low-cost traceability of complex heterogeneous authentication flows. Attached Figure Description

[0025] Figure 1 This is a diagram of the blockchain-based evidence storage and self-certification auditing system for trusted data space hybrid authentication behavior according to the present invention.

[0026] Figure 2 This is a flowchart illustrating the overall workflow of blockchain-based evidence storage for hybrid authentication behavior in this invention.

[0027] Figure 3 This is a flowchart illustrating the generation process of prime number mapping and state binding for key events in this invention.

[0028] Figure 4 This is a flowchart illustrating the non-interactive witness generation and audit node compliance verification process for the isolation dimension of this invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] See attached document Figure 1-4 This invention provides a blockchain-based evidence storage and self-certification auditing system for hybrid authentication behavior in a trusted data space. The physical entity and logical architecture are deployed within a general trusted data space (IDS) environment. The system mainly consists of an authentication requester, an authentication gateway, an accumulator execution engine, blockchain nodes, and audit nodes. The authentication requester is the entity that initiates data access or resource call requests. The authentication requester sends access messages carrying multi-dimensional attribute identifiers through a client. The authentication gateway, as the logical boundary of the data space, is configured to capture the key event stream in the hybrid authentication process. The key event stream includes the authentication method selection trajectory, identity verification results, and the triggering status of preset compliance policies.

[0031] The authentication gateway and the accumulator execution engine are logically connected. The accumulator execution engine is the core of the system's computation. It integrates a state entanglement mapping module and a trajectory recursive accumulation module. The accumulator execution engine receives event features from the authentication gateway through a communication protocol and generates entangled prime number mapping values ​​based on the current accumulation state. Blockchain nodes are distributed in the data space through a peer-to-peer network to receive and store the global trajectory feature values ​​output by the accumulator execution engine. The audit node, as an independent verification entity, performs algebraic verification by using the feature values ​​obtained from the blockchain and the witness values ​​provided by the authentication gateway after receiving an audit challenge.

[0032] The overall workflow of the blockchain-based evidence storage and self-certification auditing system based on the aforementioned trusted data space hybrid authentication behavior includes:

[0033] S101, the authentication requester initiates an access request for the target resource in the trusted data space. The access request triggers the authentication gateway to start the hybrid authentication process. During this process, the authentication gateway monitors and extracts business elements from multiple dimensions in real time. The business elements include the authentication protocol type, data security level mark and the corresponding contract execution logic.

[0034] S102, the accumulator execution engine performs system initialization, establishing an algebraic computation space based on large composite numbers. Specifically, it selects two secret large prime numbers. and Calculate the product As a modulus, the system in the modulus In a cyclic group, mutually algebraically independent generators are assigned as dimensional basis elements, including the basis used to identify authentication methods. A base for identifying data tags and the base used to identify the performance behavior Algebraic independence means that the bases are independent in terms of modularity. Under the operation, it satisfies algebraic independence, that is, any basis cannot be represented by other bases through exponentiation;

[0035] S103, the authentication gateway captures key events at each stage of hybrid authentication. and key events The data is sent to the accumulator execution engine, which uses a state entanglement mechanism to generate key events. Corresponding prime number , prime number The generation process is as follows: The currently captured key events... The accumulated state components from the previous time step The hash digest is obtained by concatenating and concatenating the hashes, and then using this hash digest as input to the hash function. The accumulator execution engine appends an iteration counter to this hash digest and performs Miller-Rabin primality checks until the first prime number that meets the preset bit width requirement is found. This mechanism ensures that every generated prime number All of them have an algebraic dependency on the states of all preceding steps;

[0036] S104, for each dimension of the authentication trajectory, the accumulator execution engine performs recursive accumulation operations, for those belonging to the dimension The event sequence, current state component Through the formula:

[0037]

[0038] Evolution occurs in this formula, Representing dimensions exist The intermediate cumulative result at each moment, for Entangled prime numbers generated at each moment;

[0039] S105, at the end of the authentication process, the accumulator execution engine synthesizes the sub-states of each dimension to generate global trajectory feature values. This characteristic value is obtained through the formula

[0040]

[0041] Perform the calculations in this formula, , , These represent the final cumulative values ​​of the authentication method dimension, data tagging dimension, and execution behavior dimension at the end of the authentication process. Since the generators of each dimension are all derived from the same modulus... Within the defined multiplicative group, the above direct modular multiplication operation can achieve feature aggregation within the same group structure; and since the generators satisfy algebraic independence, the synthesized... It will not destroy the internal algebraic structure of each dimension;

[0042] S106, the authentication gateway will generate global trajectory feature values. The data is sent to the blockchain nodes, which then use a consensus mechanism to transmit the global trajectory feature values. Packed into blocks, due to global trajectory feature values It is a fixed-length algebraic eigenvalue, and the storage overhead of the eigenvalue on the blockchain does not change as the authentication steps are extended;

[0043] S107, When the audit node receives an audit instruction, the evidence storage party calculates the witness value based on the current cumulative status. To achieve dimensional isolation auditing, if the audit target is a dimension Specific events in The evidence provider first calculates the witness value for that dimension component. And by combining the final state of other dimensions, a blinding factor is constructed. Audit nodes obtain fixed feature values ​​from the blockchain. And using the formula:

[0044]

[0045] If the two sides of the equation are completely consistent, the authentication behavior is determined to be consistent with the original record in terms of both temporal logic and attribute dimensions.

[0046] Furthermore, this invention provides a blockchain-based method for evidence storage and self-verification auditing of hybrid authentication behavior in a trusted data space. By establishing data transmission between the authentication gateway and the accumulator execution engine, it achieves evidence storage and auditing of the hybrid authentication process, specifically including:

[0047] S201, the accumulator execution engine configures global initialization parameters. The accumulator execution engine selects two large prime numbers that meet the preset safety length for multiplication to generate a modulus. The accumulator execution engine in the module Within a cyclic group, multiple algebraically independent generator bases are determined. , and These are used for the three business dimensions of authentication method, data tagging, and contract execution behavior, respectively. The accumulator execution engine sets the initial state values ​​for each business dimension. , as well as Each is assigned a value corresponding to an independent algebraic basis. , as well as ;

[0048] S202, the authentication gateway performs protocol parsing on the access request to enter the trusted data space. The authentication gateway extracts key event sequences belonging to different dimensions from the authentication stream of the access request. The key event sequences include the authentication algorithm type selected by the user, the data security level mark, and the access control policy triggering instructions. The authentication gateway sends the extracted key event sequences to the accumulator execution engine in the order of their occurrence.

[0049] S203, the accumulator execution engine performs a prime number mapping operation based on state entanglement, for the captured prime numbers belonging to the dimension. The Key events The accumulator execution engine will handle key events. With dimension The state value at the previous moment To perform cascading, the accumulator execution engine calls the prime number mapping function. Performing operations on the cascaded results, the mapping yields entangled prime numbers. The mapping process satisfies the following formula:

[0050]

[0051] In the above formula, Indicates specific business dimensions, Representing dimensions exist The event feature vector at time step, Representing dimensions exist Intermediate state value at time step Represents data cascading operations, prime number mapping function It includes hash operations and deterministic prime number search steps;

[0052] S204, the accumulator execution engine performs the recursive evolution of the dimensional state, and the accumulator execution engine generates entangled prime numbers. As an index, for dimensions The state value at the previous moment Perform modular exponentiation to update and obtain the dimension. In the present State value at time , when hour, The values ​​are algebraic independent basis of the corresponding dimension. The evolution process satisfies the following formula;

[0053]

[0054] In the above formula, The modulus represents the initialization of the system. Through this recursive exponentiation operation, the final state component of each dimension contains the order information of all authentication steps in the dimension. If the authentication steps are reversed, the entangled prime number calculated subsequently will change, causing the final state component to fail.

[0055] S205, the accumulator execution engine performs the synthesis of global trajectory feature values. At the end of the hybrid authentication process, the total number of authentication steps is defined as follows: The accumulator execution engine obtains the final state components of each dimension at the end time. , and The accumulator execution engine performs multiplication operations using the basis corresponding to each dimension to synthesize global trajectory feature values. The accumulator execution engine uses modular multiplication to aggregate the final state components of each dimension, and the synthesis process satisfies the following formula:

[0056]

[0057] In the above formula, , as well as These represent the final state values ​​after the recursive accumulation of the authentication method, data tagging, and contract execution behavior dimensions, respectively. Indicates the multiplication operation;

[0058] S206, The authentication gateway receives global trajectory feature values. And execute blockchain notarization, the authentication gateway will store the global trajectory feature values Write the notarization transaction and submit it to the blockchain network. After the blockchain nodes perform consensus verification, the notarization transaction will contain... Transactions are persistently stored in blocks;

[0059] S207, the system responds to the audit request and performs algebraic verification when the audit node needs to verify the authentication method dimension. Prime numbers corresponding to specific events in When initiating compliance verification, the evidence storage party calculates the witness value of the dimensional components. Dimensional component witness value To make the corresponding dimensions of the algebraic independent basis After The result of summing all prime numbers except those mentioned above. The proof-providing party simultaneously constructs a blinding factor. Blinding factor To divide the dimension The modulo product of the final state components of all dimensions other than the previous one. The audit node obtains the global trajectory feature values ​​from the blockchain. And verify the following verification equation:

[0060]

[0061] In this formula, Indicates excluding dimensions The modulo product of the final state components of all dimensions except the other.

[0062] Furthermore, the blockchain-based evidence storage and self-certification auditing system, which utilizes hybrid authentication behavior within a trusted data space, constructs a secure computing space based on the principle of an algebraic accumulator. This secure computing space is configured using preset global parameters, providing the computational foundation for subsequent authentication trajectory accumulation. Specifically, this includes:

[0063] S301, determine the security parameters and number domain range of the secure computation space, and the accumulator execution engine selects the bit width parameter according to the preset security strength. Bit width parameter The value of this parameter directly affects the bit width of the subsequently generated modulus. For example, when the security strength requirement is 128 bits, the bit width parameter... When set to 3072 or higher, the accumulator execution engine selects two independent large prime numbers of equal length. and ;

[0064] S302, Module for generating secure computing space The accumulator execution engine calculates two large prime numbers. and The product of the products yields the modulus. That is, satisfying the formula Modulus A modular multiplication group is defined to perform all exponentiation operations, during which large prime numbers... and The private key parameter is stored in the trusted execution environment of the accumulator execution engine, or destroyed by the execution logic after parameter configuration is completed, while the modulus... It is then published as a public parameter to the authentication gateway and audit nodes;

[0065] The S303 features a multidimensional algebraic independent basis, with an accumulator execution engine based on a modular algebraic base. Within the defined multiplicative group, a set of generators is selected, where the generators of each dimension satisfy algebraic independence, meaning that any generator cannot be represented by other generators through exponentiation. This ensures that exponentiation performed on one basis will not affect the trajectory features represented by another basis. Specifically, the accumulator execution engine selects generators respectively. Generator and generator Among them, generator As the benchmark element for the authentication method dimension, the generator As the baseline element of the data labeling dimension, the generator As a benchmark element in the dimension of contract execution behavior, the generator element Generator and generator All elements are selected as major-order elements within the multiplication group to ensure the stability of the algebraic structure. Through this basis allocation mechanism, the system maps the hybrid authentication elements to independent computational paths.

[0066] S304 defines the mapping rules from events to the prime number field. The accumulator execution engine establishes a mapping from business event characteristics to the large prime number set. The mapping relationship is deterministic, requiring that for the same input event feature vector, the mapping function must output a unique mapping value. Furthermore, to utilize the unique decomposition property of the accumulator, the mapping value corresponding to any key event must be a prime number. For a given authentication event feature vector... The mapping function transforms it into a prime number within a preset range. , prime number The lower bound of the range of values ​​is set to be greater than 3, and all generated prime numbers are distinct.

[0067] S305, Initialize the state variables of each dimension. The accumulator execution engine sets the initial value of the accumulator for each dimension to the algebraically independent basis of the corresponding dimension, that is, initialize the authentication method state components. Data label state component Contract execution behavior state components After completing the above parameter configuration, the secure computing space has the ability to process heterogeneous authentication streams. The secure computing space can not only support single-dimensional pipelined evidence storage, but also support the aggregated expression of multi-dimensional composite behaviors through the homomorphic characteristics of modular exponentiation.

[0068] Furthermore, in this embodiment of the blockchain-based evidence storage and self-certification auditing system for hybrid authentication behavior in a trusted data space, a business-dimensional algebraically independent basis mapping method is provided. By allocating mutually independent generators within a preset algebraic space, homomorphic isolation of heterogeneous business dimensions in hybrid authentication behavior is achieved. Specifically, it includes:

[0069] S401, the accumulator execution engine determines multiple business dimensions that need to be recorded based on the business logic of the general trusted data space. The business dimensions include at least the authentication method dimension, the data tag dimension, and the contract execution behavior dimension. Each dimension represents a type of logical attribute in the hybrid authentication process.

[0070] S402, accumulator execution engine in module Within the multiplication group, multiple algebraically independent elements are selected as the algebraically independent basis for the corresponding dimension. The accumulator execution engine selects the first generator as the basis for the authentication method dimension. The second generator is selected as the basis for the data labeling dimension. The third generator is selected as the basis for the contract execution behavior dimension. , base , base and base Both belong to integer modulo Multiplication group;

[0071] S403, the accumulator execution engine verifies and ensures that the basis set meets the algebraic independence requirement. Algebraic independence refers to the property that, for a selected basis set... In the model In this operation, no single basis can be represented as a product of powers of other bases. To achieve algebraic independence, the accumulator execution engine selects coprime primes as the initial base and modulo... The squaring operation maps prime numbers to quadratic residue subgroups, thus obtaining the basis. , base and base This mapping mechanism establishes the operational independence of different business elements in the algebraic space;

[0072] S404, the accumulator execution engine establishes a mapping association between business event feature vectors and algebraically independent basis powers. When the authentication gateway captures a feature vector belonging to a specific dimension... Key events At that time, the accumulator execution engine will handle critical events. Transform into the corresponding entangled prime numbers The accumulator execution engine executes entangled prime numbers. As an intermediate state value updated exponentially to the corresponding dimension, it enables the mapping of business information on a specific dimension;

[0073] S405, the accumulator execution engine utilizes homomorphism to construct global trajectory feature components for any business dimension. Dimension Trajectory components at the end of authentication It is directly equivalent to its final state component, satisfying the following formula:

[0074]

[0075] In this formula, Describe the algebraically independent basis of this dimension. Indicates the end time of authentication The product of all entangled primes in this dimension Represents the modulus and trajectory components. Dimensions were recorded Complete causal sequence information;

[0076] S406, the accumulator execution engine performs homomorphic aggregation of trajectory components in each dimension, and then uses modular multiplication to convert the trajectory components... Trajectory components and trajectory components Aggregates into global trajectory feature values Since the basis sets satisfy algebraic independence, the global trajectory eigenvalues It enables the algebraic composition of multi-dimensional information, allowing subsequent audits to extract the cumulative state of a specific dimension without touching the plaintext of other dimensions. Specifically, when considering a dimension... During auditing, the audit node can obtain global trajectory feature values ​​from known trajectory components in other dimensions. Separate from the dimensions The power structure.

[0077] Furthermore, in this embodiment of the blockchain-based evidence storage and self-certification auditing system based on trusted data space hybrid authentication behavior, a method for generating prime number entanglement for key events is disclosed. By binding the real-time captured business event features with the algebraic state of the system, the method ensures that the generated prime number sequence has a time-dependent attribute, specifically including:

[0078] S501, the authentication gateway captures data belonging to a specific business dimension. Current authentication event characteristics Authentication event characteristics It contains decision data from the hybrid authentication process. The decision data includes the identifier code of the authentication algorithm, the status bit of the verification result, and the trigger parameters of the security policy. The authentication gateway converts the decision data into a fixed-length binary feature vector through a feature extraction algorithm. Specifically, the authentication gateway arranges the decision data according to the preset field order and performs truncation or padding on non-fixed-length fields to generate a binary feature vector.

[0079] S502, the accumulator execution engine retrieves business dimensions from the storage unit. Intermediate state value at the previous moment intermediate state values Up to the current step, in terms of business dimensions The algebraic cumulative value of all historical authentication behaviors is obtained by introducing intermediate state values. As input variables, the algebraic dependency of the mapping value generated by the current event on the historical trajectory is realized;

[0080] S503, the accumulator execution engine performs a feature cascading operation, which sets the current authentication event features... Intermediate state value compared to the previous time step Perform bit concatenation to generate the concatenated original data block. In the cascaded original data blocks In the middle, the current authentication event characteristics At a high level, the intermediate state value of the previous moment. At a low level, cascading operations establish a parameter association between the current behavior and the historical state. Modifications to the historical trajectory will very likely cause the verification of the current mapping value derived from that state to fail.

[0081] S504, the accumulator execution engine processes raw data blocks. To perform a deterministic prime mapping, the accumulator execution engine calls a predefined one-way hash function on the original data block. The calculation yields an initial hash digest. The accumulator execution engine then converts this hash digest into an initial integer and, starting with this initial integer, performs a search within the integer space in increments of 1. During the search, the accumulator execution engine performs primality checks on each selected integer until the first prime number is found, denoted as the entangled prime number. Entangled prime numbers The generation process satisfies the following formula:

[0082]

[0083] In the above formula, Representing dimensions exist Entangled prime numbers generated at each moment; Representing dimensions exist The characteristics of authentication events at any given moment; Representing dimensions exist Intermediate state value at any given time; This indicates a data cascading and splicing operation; This represents a one-way hash function; This indicates the logic of performing an incremental search starting from the hash calculation result and outputting the first prime number;

[0084] S505, accumulator execution engine outputs entangled prime numbers. And pass it to the trajectory recursive accumulation module to entangle prime numbers. Represents the characteristics of authentication events The content, and defined the characteristics of the authentication event. In the overall authentication flow, since the mapping process of each dimension is independently executed to generate prime number entanglement, the system can generate prime number sequences that are independent and logically consistent for different business dimensions.

[0085] Furthermore, in this embodiment of the blockchain-based evidence storage and self-certification auditing system for hybrid authentication behavior in trusted data space, an algebraic recursive accumulation method for authentication trajectories is disclosed. By performing exponential nesting under modular arithmetic, discrete events in the hybrid authentication process are transformed into algebraic components with causal dependencies. The algebraic recursive accumulation process is executed in parallel or asynchronously by the accumulator execution engine for different business dimensions, specifically including:

[0086] S601, the accumulator execution engine obtains the current time. Generated entangled prime numbers Entangled prime numbers Belonging to a specific business dimension And entangled prime numbers Includes business dimensions In the previous moment The accumulator execution engine transmits the status information of entangled primes via the data bus. Loaded into the exponent register of the arithmetic logic unit;

[0087] S602, the accumulator execution engine retrieves the business dimensions recorded in memory. intermediate state values intermediate state values As the base for this modular exponentiation operation, it is used at the beginning of the authentication process, i.e. At that time, intermediate state value Assigning values ​​to business dimensions Corresponding algebraic independent basis By setting the initial base as an algebraically independent basis This ensures that all entangled primes generated subsequently are within the business dimension. Accumulate within the algebraic space;

[0088] S603, the accumulator execution engine executes state evolution based on modular exponentiation. The accumulator execution engine uses intermediate state values... Using the base as the base, to entangle prime numbers As an exponent, in the model The state components at the current moment are calculated within the space. The state evolution process satisfies the following formula:

[0089]

[0090] In the above formula, Indicates business dimension At any moment The accumulated state components; Indicates business dimension At any moment The accumulated state components; Representing dimensions At any moment The generated and entered entangled prime numbers; This represents the preset module of the secure computing space;

[0091] S604, the accumulator execution engine calculates the current state component obtained at the current moment. When performing an update operation, the accumulator execution engine will process the state components. The data is overwritten into the corresponding dimension's state register, serving as the base input for the next recursive accumulation. This recursive accumulation mechanism establishes the unidirectional evolutionary characteristic of the authentication trajectory at the algebraic level. Due to the nested relationship of exponentiation operations, the state components... Complete record of business dimensions Mathematical characteristics of all historical authentication steps;

[0092] In step S605, the accumulator execution engine determines whether the authentication event stream of the current dimension has ended. If the authentication gateway detects subsequent key events, it repeats steps S601 to S604. If the authentication process terminates, the accumulator execution engine outputs the final accumulated state component as the final feature value of the dimension. Since the entangled prime number generated in each step is based on the previous state as a parameter, the final feature value not only proves the existence of all events, but also locks the causal order of events through the nested structure of algebraic powers.

[0093] Furthermore, in this embodiment of the blockchain-based evidence storage and self-certification auditing system for hybrid authentication behavior in trusted data space, a global trajectory feature value synthesis method is disclosed. This method generates a fixed-length feature value that can characterize the trajectory features of the entire hybrid authentication process by algebraically aggregating trajectory feature components from different business dimensions. Specifically, it includes:

[0094] S701, the accumulator execution engine obtains the final state components of each business dimension at the end of the hybrid authentication process. The final state components include the state components of the authentication method dimension. State components of data labeling dimensions and the state components of the contract execution behavior dimension State components , as well as The causal logic evolution results of events within each dimension were recorded separately;

[0095] S702, the accumulator execution engine directly processes the final state component , as well as Defined as trajectory feature components of the corresponding dimension, since the initial state has been set as an algebraically independent basis and subsequent modular exponentiation based on entangled primes is performed, the final state components of each business dimension are... as well as These already represent the trajectory features of their respective dimensions. The accumulator execution engine directly processes the state components. as well as Defined as the first eigencomponent Second characteristic component With the third characteristic component The calculation logic is as follows:

[0096] ;

[0097] ;

[0098]

[0099] In the above formula, , , Each dimension represents the time at the end. State components; The modulus initialized for safe computation space;

[0100] S703, the accumulator execution engine performs the synthesis operation of global trajectory feature values. The accumulator execution engine uses modular multiplication to perform the first feature component. Second characteristic component and the third characteristic component Aggregation is performed to obtain global trajectory feature values. The composition operation satisfies the following formula:

[0101]

[0102] In this formula, Indicates business dimension The final state value after the recursive accumulation is due to the basis. , , Satisfying algebraic independence, global trajectory eigenvalues By mapping authentication trajectories of different dimensions to mutually independent algebraic subspaces, this synthetic structure allows for the mapping of authentication trajectories in a given dimension. When performing an isolated audit, the evidence provider can provide evidence in addition to dimensions. The modular product of feature components other than those in other dimensions is used as a blinding factor, allowing audit nodes to operate without knowing the plaintext information of key events in other dimensions, and only by processing the feature components of the encrypted or aggregated state. Verification dimension of the algebraic relationship with the blinding factor This ensures compliance, thereby preventing cross-dimensional plaintext leakage of business data while guaranteeing the validity of equation verification.

[0103] S704, the accumulator execution engine processes the generated global trajectory feature values. The accumulator execution engine performs formatting processing and converts the global trajectory feature values. It is converted into a binary data stream that meets the requirements of the blockchain evidence storage interface, and a unique transaction identifier for the current business request is appended to the binary data stream. The formatting process ensures the parsability of the feature value data in the distributed ledger.

[0104] S705, the accumulator execution engine processes the global trajectory feature values. Output to the authentication gateway, global trajectory feature value As algebraic evidence of hybrid authentication behavior, it is sent to the blockchain node for persistent recording, due to global trajectory feature values. The length is determined by the modulus The bit width determines the fixed-length compression of multi-dimensional authentication data, and the global trajectory feature value synthesis method achieves this. The length does not change as the number of authentication events increases.

[0105] Furthermore, this embodiment discloses an on-chain immutable evidence storage mechanism for a blockchain-based evidence storage and self-verification audit system based on hybrid authentication behavior in a trusted data space. By combining global trajectory feature values ​​generated through algebraic operations with the distributed ledger technology of the blockchain, persistent storage and association of evidence related to hybrid authentication behavior are achieved. Specifically, this includes:

[0106] S801, the authentication gateway obtains the global trajectory feature values ​​output by the accumulator execution engine. The authentication gateway extracts the associated metadata of the current hybrid authentication transaction, which includes the identifier of the access requester. Identifier for accessing the target resource Authentication completion timestamp and globally unique transaction identifier Globally unique transaction identifier To distinguish different authentication batches initiated by the same requesting subject, the authentication gateway will use global trajectory feature values. Encapsulate the associated metadata to generate the original evidence storage data packet;

[0107] S802, the authentication gateway performs an electronic signature on the original data packet for evidence storage. The authentication gateway calls the private key stored in the security module to calculate the hash value of the original data packet for evidence storage and generate an evidence storage transaction message with proof of origin. The electronic signature ensures the integrity of the evidence storage data during the transmission to the blockchain network.

[0108] S803, the authentication gateway broadcasts the evidence storage transaction message to the blockchain network. The consensus node in the blockchain network receives the evidence storage transaction message and calls the public key of the authentication gateway to verify the validity of the electronic signature. After the verification is passed, the consensus node sorts the evidence storage transaction message according to the preset consensus algorithm, and the blockchain node records the evidence storage transaction message in the block to be generated.

[0109] S804, blockchain nodes achieve persistent storage of feature values ​​by executing a notarization smart contract. The notarization smart contract defines a mapping table structure in the blockchain's state database and receives global trajectory feature values ​​from the original notarization data packet. and globally unique transaction identifier And perform the following storage operations:

[0110]

[0111] In the above formula, This represents the key-value pair mapping relationship defined in the evidence storage smart contract. As the key for storing the index, As stored data values, the evidence-keeping smart contract writes the mapping relationship into the block's state tree, enabling auditing nodes to retrieve globally unique transaction identifiers. Retrieve the corresponding global trajectory feature values ;

[0112] S805, the evidence storage smart contract executes an asynchronous notification mechanism. After the data is written to the state database, the evidence storage smart contract generates a block height, transaction hash, and global trajectory feature value. The event log summary serves as an interface for external systems to perceive the evidence storage results, allowing audit nodes to retrieve evidence storage entries in subsequent audit processes. Through the above steps, this embodiment transforms complex hybrid authentication behaviors into fixed-length algebraic feature values ​​and uploads them to the blockchain. Due to the chain structure of the blockchain, the global trajectory feature values ​​stored in the state database... It possesses immutability; even if the authentication gateway or accumulator execution engine fails at a later time, the global trajectory feature value stored in the block will remain unchanged. It can still serve as a mathematical benchmark for determining the authenticity of historical trajectories.

[0113] Furthermore, in this embodiment of the blockchain-based evidence storage and self-certification auditing system based on hybrid authentication behavior in trusted data space, a non-interactive witness generation method with isolated dimensions is disclosed. This method utilizes the membership proof characteristics of algebraic accumulators and the homomorphic separation properties of multidimensional algebraic independent basis to achieve verification of key events in a specific dimension without disclosing the specific content of non-target dimensions. Specifically, this includes:

[0114] S901, The evidence storage party receives an audit challenge instruction, which includes the identifier of the business dimension to be audited. And the target events to be audited in the business dimension Timing position in The evidence storage party identifies the evidence based on business dimensions. Retrieve the corresponding entangled prime number sequence from memory. Entangled prime number sequences Recorded business dimensions All entangled prime numbers from the start to the end of the certification process;

[0115] S902, the evidence depositor calculates the witness value of the dimensional component. The evidence depositor first determines the dimensional exclusion product. Dimension Exclusion Product For entangled prime number sequences except those in temporal positions Target entangled primes The product of all entangled primes except for the one mentioned above, the evidence is stored from a business perspective. Corresponding algebraic independent basis Using the base, exclude the product by dimension. As an exponent, in the model The witness value of the dimensional component is obtained by performing an exponentiation operation within the space. Dimensional component witness value The calculation formula is as follows:

[0116]

[0117] In the above formula, Indicates business dimension The corresponding generative basis; The module configured for secure computing space; Due to the witness value of the dimension component The target entangled prime number was excluded at the exponential position. Dimensional component witness value This constitutes the target entangled prime number Members provide evidence;

[0118] S903, the evidence storage party constructs a blinding factor for the isolation dimension. This allows the audit node to reconstruct the global trajectory feature value without knowing the specific authentication trajectory of non-target dimensions. The evidence storage party retrieves data excluding business dimensions. The final feature components of all other dimensions except for, specifically, for any dimension and The evidence storage party obtains the final feature components of the corresponding dimension. The evidence storage party defines the modular product of all auxiliary feature components as the blinding factor. Blinding factor The construction of satisfies the following formula:

[0119]

[0120] In the above formula, Indicates non-audit dimensions The final trajectory feature components, blinding factor Aggregates algebraic states from all non-audit dimensions, and includes a blinding factor. Used to mask plaintext information from non-audit dimensions during the verification process;

[0121] S904, the witnessing party sends the generated witness dataset to the audit node. The witness dataset contains dimensional component witness values. Blinding factor And the target entangled prime number to be verified Since the witness dataset consists of the results of algebraic operations and does not contain the original authentication features or plaintext attributes of non-target dimensions, dimensional isolation is achieved in the audit process.

[0122] S905, the audit node performs an algebraic consistency check, and the audit node obtains the pre-fixed global trajectory feature value from the blockchain. The audit node uses parameters from the witness dataset to verify the target entangled prime number. With global trajectory feature values The logical relationship is such that the verification process satisfies the following verification equation:

[0123]

[0124] If the verification equation holds, then the target entangled prime number is determined. The corresponding authentication events actually exist in the business dimension. In the authentication trajectory.

[0125] Furthermore, in this embodiment of the blockchain evidence storage and self-certification audit system based on hybrid authentication behavior in trusted data space, a compliance verification and judgment method for audit nodes is disclosed. This method involves the audit node performing an algebraic comparison between the blockchain evidence storage data and the witness data provided by the evidence storage party to prove the content integrity and temporal compliance of the hybrid authentication behavior. Specifically, this includes:

[0126] S1001, after receiving an audit task for a specific business transaction, the audit node uses a globally unique transaction identifier. Retrieve pre-defined global trajectory feature values ​​from the blockchain's state database. The audit node obtains global trajectory feature values ​​by accessing the distributed ledger interface of the blockchain node. To ensure global trajectory feature values Unaltered;

[0127] S1002, the audit node obtains the verification dataset sent by the evidence storage party. The verification dataset contains the dimensional component witness values. Target entangled prime numbers Blinding factor Key events to be audited (explicit text) and preceding intermediate state components Dimensional component witness value In terms of business dimension Subtract the target entangled prime from the accumulated trajectory The subsequent algebraic state, blinding factor The product of trajectory feature components corresponding to non-audit dimensions;

[0128] S1003, Audit node execution target entangled prime number For consistency verification, the audit node will transmit key events in plaintext. With the preceding intermediate state components The numbers are concatenated according to the preset cascading rules, and the prime number mapping function defined during the system initialization phase is called. The reference prime number is recalculated, and the audit node compares the reference prime number with the target entangled prime number in the verification dataset. Are they consistent? If they are inconsistent, then the business dimension should be determined. If the authentication trajectory is found to have been tampered with or its timing falsified, the audit will be terminated.

[0129] S1004, entangled prime numbers in the target After passing the consistency check, the module configured in the secure computing space by the audit node... In this environment, exponentiation and combination operations are performed, and audit nodes witness values ​​using dimensional components. Using the base as the target, entangle the prime numbers. Modular exponentiation is performed on the exponent, and then the audit node combines the intermediate results of the modular exponentiation with the blinding factor. Perform modular multiplication to reconstruct the local validation value;

[0130] S1005, the audit node compares the reconstructed local verification value with the retrieved global trajectory feature value. The comparison and verification are based on the mathematical logic that satisfies the following verification formula:

[0131]

[0132] In the above formula, Indicates business dimension In time sequence position The dimensional component witness value; This represents the target entangled prime number after consistency verification; Indicates excluding dimensions Blinding factors for all non-audit dimensions except those mentioned above; This represents the global trajectory feature value obtained from the blockchain; The modulus representing the secure computation space;

[0133] S1006, the audit node outputs a compliance judgment conclusion based on the comparison results. If the verification formula equation holds true, the key event plaintext is determined. True global trajectory feature values Within the recorded authentication trajectory, and in plaintext of key events. The order of occurrence and the preceding intermediate state components The temporal logic of the representation is consistent; if the equation does not hold, then the business dimension is determined. The authentication trajectory is non-compliant because the target is bound to a prime number. If the state binding mapping has been performed during the generation phase, changes to the preceding steps will cause the recalculated reference prime number to deviate from the original mapping trajectory by a very high probability, thus failing the subsequent algebraic verification.

Claims

1. A blockchain-based method for evidence storage and self-verification auditing of trusted data space hybrid authentication behavior, characterized in that, Includes the following steps: The accumulator execution engine configures global initialization parameters, generates a modulus, and determines multiple algebraically independent generator bases within the loop group to correspond to multiple business dimensions. The initial state values ​​of each business dimension are assigned to the corresponding generator bases. The authentication gateway performs protocol parsing on the access request, extracts key event sequences belonging to different business dimensions, and sends them to the accumulator execution engine. The accumulator execution engine performs a prime number mapping operation based on state entanglement, concatenating the captured key events with the state values ​​of the corresponding business dimensions at the previous time step to obtain entangled prime numbers. The accumulator execution engine performs a recursive evolution of the execution dimension state, using the entangled prime number as an exponent to perform a modular exponentiation operation on the previous state value of the corresponding business dimension, and updates the current state value. At the end of the hybrid authentication process, the accumulator execution engine uses the final state components of each business dimension at the end time and the corresponding generator basis to synthesize the global trajectory feature value. The authentication gateway receives the global trajectory feature value and performs blockchain-based evidence storage; In response to an audit request, the evidence custodian calculates the witness value and constructs the final blinded component, which is then sent to the audit node. The audit node obtains the global trajectory feature value from the blockchain and performs algebraic verification.

2. The blockchain-based evidence storage and self-verification auditing method for trusted data space hybrid authentication behavior as described in claim 1, characterized in that, The multiple business dimensions include at least the authentication method dimension, the data tagging dimension, and the contract execution behavior dimension; The accumulator execution engine is configured with global initialization parameters, specifically including: The modulus is generated by multiplying two large prime numbers. Within the multiplication group defined by the modulus, the first generator, the second generator, and the third generator, which satisfy algebraic independence, are selected as algebraic independent basis for the authentication method dimension, the data tagging dimension, and the contract execution behavior dimension, respectively.

3. The blockchain-based evidence storage and self-verification auditing method for trusted data space hybrid authentication behavior as described in claim 1, characterized in that, The accumulator execution engine performs prime number mapping operations based on state entanglement and recursive evolution of dimensional states, satisfying the following algebraic formula: ； ； in, Indicates specific business dimensions, Indicates time, Indicates business dimension exist The key events at any given moment are transformed into feature vectors. Indicates business dimension exist Intermediate state value at time step This indicates a data cascading operation. Represents the prime number mapping function, This represents the entangled prime number obtained by the mapping. Represents the modulus, This indicates the business dimension obtained from the update. In the present The state value at any given moment.

4. The blockchain-based evidence storage and self-verification auditing method for hybrid authentication behavior in a trusted data space as described in claim 3, characterized in that, The prime number mapping function includes hash operations and deterministic prime number search steps; the execution of the prime number mapping operation based on state entanglement specifically includes: An initial hash digest is obtained by calculating the concatenation result of the feature vector and the intermediate state value using a one-way hash function; The initial hash digest is converted into an initial integer, and starting from the initial integer, an incremental search and Miller-Rabin primality test are performed in the integer space with a preset step size until the first prime number that meets the bit width requirement is obtained, which is then output as the entangled prime number.

5. The blockchain-based evidence storage and self-verification auditing method for trusted data space hybrid authentication behavior as described in claim 1, characterized in that, The accumulator execution engine performs the synthesis of global trajectory feature values, specifically as follows: Define the total number of authentication steps and obtain the final state components of each business dimension at the end time; Using the base of the generator corresponding to each business dimension as the base and the final state component of each business dimension as the exponent, perform exponentiation operations respectively; Perform a series of multiplication operations on the final state components of all business dimensions in the modular space to generate the global trajectory feature value of fixed length.

6. The blockchain-based evidence storage and self-verification auditing method for hybrid authentication behavior in a trusted data space as described in claim 1, characterized in that, The authentication gateway receives the global trajectory feature value and performs blockchain notarization, specifically including: The authentication gateway extracts the associated metadata of the current hybrid authentication transaction. The associated metadata includes the identifier of the access requester, the identifier of the access target resource, the timestamp of authentication completion, and the globally unique transaction identifier. The authentication gateway encapsulates the global trajectory feature value and the associated metadata, generates the original data packet for evidence storage, performs electronic signature to generate the evidence storage transaction message, and broadcasts it to the blockchain network; By executing the evidence storage smart contract, the blockchain node persists the global trajectory feature value as the stored data value into the state tree of the block, using the globally unique transaction identifier as the key of the storage index in the mapping table structure of the state database.

7. The blockchain-based evidence storage and self-verification auditing method for hybrid authentication behavior in a trusted data space as described in claim 1, characterized in that, The evidence storage party calculates the witness value and constructs the final blinded component before sending it to the audit node, specifically including: The evidence storage party receives an audit challenge instruction containing the identifier of the business dimension to be audited and the temporal position of the target event in the business dimension, and retrieves the corresponding entangled prime number sequence; Calculate the dimension exclusion product, which is the product of all entangled primes in the entangled prime sequence except for the target entangled prime at the time position; Using the base of the generator element corresponding to the business dimension to be audited as the base, and the product of the excluded dimensions as the exponent, the power operation is performed in the modulus space to obtain the witness value of the dimension component. Obtain the final feature components of all other business dimensions besides the business dimension to be audited, define the modular product of all final feature components as the blinding factor, and send the witness dataset containing the witness values ​​of the dimension components and the blinding factor to the audit node.

8. The blockchain-based evidence storage and self-verification auditing method for hybrid authentication behavior in a trusted data space as described in claim 7, characterized in that, The audit node obtains the global trajectory feature value from the blockchain and performs algebraic verification, satisfying the following verification equation: ； in, Indicates the business dimensions to be audited. In time sequence position The dimensional component witness value, Denotes the target entangled prime number. This represents the blinding factor. This represents the global trajectory feature value obtained from the blockchain. Represents the modulus; If the verification equation holds true, it is determined that the authentication event corresponding to the target entangled prime number is real and its timing has not been tampered with.

9. The blockchain-based evidence storage and self-verification auditing method for hybrid authentication behavior in a trusted data space as described in claim 8, characterized in that, Before performing algebraic verification by executing the aforementioned verification equation, the audit node also performs a consistency check on the target entangled prime number, specifically: The audit node concatenates the plaintext of the key event to be audited with the preceding intermediate state components according to a preset concatenation rule, and calls the prime number mapping function to recalculate the reference prime number; The reference prime number is compared with the target entangled prime number in the witness dataset. If they are inconsistent, it is determined that the authentication trajectory has been tampered with or the timing has been forged, and the audit is terminated.

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