Blockchain trusted sensor implementation method and system based on mimetic hashing technology

Abstract

The present invention discloses a blockchain trusted sensor implementation method and system based on mimetic hash technology, which uses a blockchain trusted sensor to collect source data, uses a hash algorithm to perform preliminary hash processing on the source data, and forwards the processed source data to a convergence router; uses a convergence router to aggregate the processed source data, and after verifying the data set, uploads it to an edge blockchain; uses a mimetic hash system in the edge blockchain to cleanse the verified data set according to a network request to obtain cleaned data, uses the mimetic hash system to process the cleaned data according to the mimetic hash algorithm, and uploads the final data to a data blockchain for storage, adds dynamic and heterogeneous components to the original data integrity verification based on static isomorphism, enhances the security of data integrity verification, and further ensures the authenticity of the data on the blockchain and the reliability of the data source, thereby ensuring the consistency of blockchain data on and off the chain.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to a blockchain trusted sensor implementation method and system based on mimetic hashing technology. Background Art

[0002] The rapid development of blockchain technology has attracted widespread attention from various industries. As a distributed ledger technology, blockchain has enabled decentralization, immutability, and traceability for traditional Internet, Internet of Things, Internet of Vehicles and other fields, while providing reliable data storage services. However, since blockchain is a relatively closed system, it is difficult to interact directly with external data. External data often needs to be processed before being sent to the blockchain, which makes it difficult to ensure the credibility of the data source and the consistency between the chain and the off-chain. At the same time, in current blockchain-based application solutions, especially in the fields of Internet of Things, Internet of Vehicles, artificial intelligence, etc., the credibility of the data source will directly affect the correctness of the core decision-making layer. Therefore, there is an urgent need to solve the problem of on-chain and off-chain consistency of blockchain data.

[0003] In addition, mimicry defense is a new network security defense technology whose core is dynamic heterogeneous redundancy. It can achieve information migration between different state spaces by actively changing the state of the components of the information system. Currently, a hash function-based integrity verification system is commonly used to solve data consistency issues. This approach can be understood as a simple, isomorphic static structure, where nodes use the same hash function for each transmission and verification. The proof algorithm used by sensor networks, Internet of Vehicles, Internet of Things, and other networks to provide integrity verification for transmitted data is such a homogeneous, static structure. This structure provides convenience for attackers and is a major reason why the current hash function-based integrity verification system faces security threats. This method also cannot effectively solve the problem of on-chain and off-chain consistency of blockchain data. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a blockchain trusted sensor implementation method and system based on mimetic hash technology, which can ensure the consistency of blockchain data on and off the chain.

[0005] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0006] A blockchain trusted sensor implementation method based on mimetic hashing technology includes the following steps:

[0007] Use blockchain trusted sensors to collect source data, use a hash algorithm to perform preliminary hash processing on the source data, and forward the processed source data to the aggregation router;

[0008] Aggregating the processed source data using the aggregation route to obtain a data set, and verifying the data set before uploading it to the edge blockchain;

[0009] Using the mimetic hash system in the edge blockchain to cleanse the verified data set according to the network request to obtain cleansed data;

[0010] The cleaned data is processed using the mimetic hash system according to the mimetic hash algorithm to obtain final data, and the final data is uploaded to the data blockchain for storage.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] A blockchain trusted sensor implementation system based on mimetic hashing technology includes blockchain trusted sensors, converged routing, edge blockchain, and data blockchain.

[0013] The blockchain trusted sensor is used to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router;

[0014] The aggregation router is used to verify the aggregated data set and upload it to the edge blockchain;

[0015] The edge blockchain includes a mimetic hash system for cleaning the verified data set according to the network request to obtain cleaned data, processing the cleaned data using a mimetic hash algorithm to obtain final data, and uploading the final data to the data blockchain;

[0016] The data blockchain is used to store the final data.

[0017] The beneficial effects of the present invention are: using blockchain trusted sensors to collect source data, and using a hash algorithm to perform preliminary hash processing on the source data, and forwarding the processed source data to the aggregation route; using the aggregation route to aggregate the processed source data to obtain a data set, and after verifying the data set, uploading it to the edge blockchain, using the mimetic hash system in the edge blockchain to clean the verified data set according to the network request to obtain the cleaned data, using the mimetic hash system to process the cleaned data according to the mimetic hash algorithm, and uploading the final data to the data blockchain for storage, thereby combining the data integrity verification based on mimetic hash technology in the blockchain trusted sensor with the idea of ​​mimetic defense, adding dynamic and heterogeneous components to the original data integrity verification based on static isomorphism, and constructing a dynamic heterogeneous blockchain sensor data security transmission and integrity verification scheme, thereby enhancing the security of data integrity verification, thereby ensuring the authenticity of the blockchain data and the reliability of the data source, thereby ensuring the consistency of the blockchain data chain and off-chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flowchart of a method for implementing a blockchain trusted sensor based on mimetic hashing technology according to an embodiment of the present invention;

[0019] Figure 2 This is a structural diagram of a blockchain trusted sensor implementation system based on mimetic hashing technology according to an embodiment of the present invention;

[0020] Figure 3 This is a system architecture diagram of a blockchain trusted sensor implementation system based on mimetic hashing technology in an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of the deployment of a blockchain trusted sensor implementation method based on mimetic hashing technology according to an embodiment of the present invention;

[0022] Figure 5 Schematic diagram of data interaction in a blockchain trusted sensor implementation method based on mimetic hashing technology according to an embodiment of the present invention;

[0023] Figure 6 Schematic diagram of mimetic hash processing in a blockchain trusted sensor implementation method based on mimetic hash technology according to an embodiment of the present invention;

[0024] Figure 7 This is a diagram of the mimetic hash system architecture in a blockchain trusted sensor implementation system based on mimetic hash technology according to an embodiment of the present invention;

[0025] Figure 8This is a schematic diagram of a request distribution module in a blockchain trusted sensor implementation system based on mimetic hashing technology according to an embodiment of the present invention;

[0026] Figure 9 This is a schematic diagram of the structure of a dynamic executor scheduler in a blockchain trusted sensor implementation system based on mimetic hashing technology according to an embodiment of the present invention;

[0027] Figure 10 This is a schematic diagram of the structure of a central scheduler in a blockchain trusted sensor implementation system based on mimetic hashing technology according to an embodiment of the present invention;

[0028] Figure 11 This is a schematic diagram of the mimetic hashing technology system in a blockchain trusted sensor implementation method based on mimetic hashing technology in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0030] Please refer to Figure 1 The embodiment of the present invention provides a blockchain trusted sensor implementation method based on mimetic hashing technology, comprising the steps of:

[0031] Use blockchain trusted sensors to collect source data, use a hash algorithm to perform preliminary hash processing on the source data, and forward the processed source data to the aggregation router;

[0032] Aggregating the processed source data using the aggregation route to obtain a data set, and verifying the data set before uploading it to the edge blockchain;

[0033] Using the mimetic hash system in the edge blockchain to cleanse the verified data set according to the network request to obtain cleansed data;

[0034] The cleaned data is processed using the mimetic hash system according to the mimetic hash algorithm to obtain final data, and the final data is uploaded to the data blockchain for storage.

[0035] From the above description, it can be seen that the beneficial effects of the present invention are: using blockchain trusted sensors to collect source data, and using a hash algorithm to perform preliminary hash processing on the source data, and forwarding the processed source data to the aggregation route; using the aggregation route to aggregate the processed source data to obtain a data set, and after verifying the data set, uploading it to the edge blockchain, using the mimetic hash system in the edge blockchain to clean the verified data set according to the network request to obtain the cleaned data, using the mimetic hash system to process the cleaned data according to the mimetic hash algorithm, and uploading the final data to the data blockchain for storage, thereby combining the data integrity verification based on mimetic hash technology in the blockchain trusted sensor with the idea of ​​mimetic defense, adding dynamic and heterogeneous components to the original data integrity verification based on static isomorphism, and constructing a dynamic heterogeneous blockchain sensor data security transmission and integrity verification scheme, thereby enhancing the security of data integrity verification, thereby ensuring the authenticity of the blockchain data and the reliability of the data source, thereby ensuring the consistency of the blockchain data chain and off-chain.

[0036] Furthermore, the using the mimetic hash system to process the cleaned data according to the mimetic hash algorithm to obtain final data includes:

[0037] Distributing the network request to a plurality of target heterogeneous executors in a heterogeneous executor pool of the mimetic hash system using the mimetic hash system;

[0038] Using multiple target heterogeneous executors in the heterogeneous executor pool to simultaneously execute a hash algorithm on the cleaned data to obtain multiple hash results, and sending the multiple hash results to a response redundancy voter of the mimetic hash system;

[0039] Using the response redundancy voter to perform cross-decision on the multiple hash results according to a voting algorithm to obtain a decision result, and sending the decision result to the central scheduler of the mimetic hash system;

[0040] The central scheduler is used to generate a scheduling strategy as final data according to the arbitration result and a preset execution body scheduling algorithm, and the multiple target heterogeneous execution bodies are updated according to the scheduling strategy.

[0041] From the above description, it can be seen that the mimetic hashing processing is jointly completed by using a heterogeneous executor pool, a central scheduler and a response redundancy voter. A dynamic heterogeneous redundant architecture is adopted, and the mimetic camouflage strategy is applied to the multi-mode arbitration, output agency, input distribution, feedback control and multi-dimensional dynamic reconstruction of the executor of the dynamic heterogeneous redundancy. This makes the defense environment have the inherent properties of "uncertainty, lockability, controllability and difficulty in coordination". It can not only provide point-to-surface fusion defense that is unrelated to attack behavior and feature information, but also effectively disintegrate the situation of coordinated attack achieved through trial and error or elimination method, thereby ensuring data security.

[0042] Furthermore, it also includes:

[0043] The monitoring module in the mimetic hash system is used to monitor the blockchain trusted sensor and network status, obtain monitoring results, and generate scheduling parameters based on the monitoring results.

[0044] From the above description, it can be seen that the monitoring module is used to monitor the blockchain trusted sensors and network status, so as to timely discover loopholes or problems in the system and improve the security of the entire system.

[0045] Furthermore, the monitoring module in the mimetic hash system is used to monitor the blockchain trusted sensor and network status, and the monitoring results obtained include:

[0046] The monitoring module in the mimetic hash system is used to monitor the energy state, data consistency state and online state of the blockchain trusted sensor, and to monitor the network traffic state, network transmission state and network security state to obtain monitoring results.

[0047] From the above description, it can be seen that the energy status, data consistency status and online status of blockchain trusted sensors are monitored separately, and the network traffic status, network transmission status and network security status are monitored separately. Monitoring can be carried out from multiple aspects of blockchain trusted sensors and network status, which improves the comprehensiveness and effect of monitoring and ensures the security of the data collection and chain-up process.

[0048] Furthermore, before using the blockchain trusted sensor to collect source data, the method further includes:

[0049] Access to multiple heterogeneous operating systems, multiple heterogeneous execution environments, and multiple heterogeneous hashing algorithms;

[0050] A plurality of heterogeneous execution bodies are formed according to the plurality of heterogeneous operating systems, the plurality of heterogeneous execution environments and the plurality of heterogeneous hash algorithms, and a heterogeneous execution body pool is generated according to the plurality of heterogeneous execution bodies.

[0051] From the above description, it can be seen that constructing a heterogeneous executable body by permuting and combining the hash algorithm, execution environment and operating system greatly improves the complexity and security of the system and reduces the probability of attackers destroying the system by attacking the hash algorithm.

[0052] Furthermore, updating the multiple target heterogeneous executables according to the scheduling strategy includes:

[0053] Using the central scheduler to send the scheduling policy to the dynamic executor scheduler in the heterogeneous executor pool;

[0054] The dynamic executable scheduler is used to monitor the status of the heterogeneous executables, and the multiple target heterogeneous executables are updated according to the scheduling strategy.

[0055] From the above description, it can be seen that the Dynamically Executing Scheduler (DES) is a control and management unit for the status of heterogeneous executors. Using the dynamic executor scheduler to monitor the status of heterogeneous executors and update multiple target heterogeneous executors according to the scheduling strategy can ensure the security of the executors, perform pseudo-heterogeneous scheduling on the executors in the pool, further enhance the differences between executors participating in the same redundancy vote, and ultimately make the system converge to a stable state.

[0056] Furthermore, after updating the multiple target heterogeneous executables according to the scheduling strategy, the method further includes:

[0057] The dynamic execution body scheduler is used to receive the decision result sent by the central scheduler, and according to the decision result, an event or timing trigger strategy is used to clean or roll back the heterogeneous execution body.

[0058] As can be seen from the above description, using events or timed triggering strategies to clean or roll back heterogeneous executors according to the adjudication results can ensure the integrity of the executors and thus improve the security and complexity of the system.

[0059] Furthermore, before using the blockchain trusted sensor to collect source data, the method further includes:

[0060] The data blockchain is deployed to the cloud side, the edge blockchain is deployed to the edge side, and the blockchain trusted sensor and the aggregation router are deployed to the end side.

[0061] From the above description, we can see that referring to the cloud-edge architecture deployment and implementing the master-slave collaborative chain architecture design can prevent data loss on a single host and improve data security.

[0062] Furthermore, it also includes:

[0063] The edge blockchain is used to periodically overwrite historical data according to its own storage space upper limit.

[0064] From the above description, it can be seen that the edge blockchain can be used to continuously process data to ensure the sustainability of the system.

[0065] A system for implementing the above method includes a blockchain trusted sensor, a converged router, an edge blockchain, and a data blockchain:

[0066] The blockchain trusted sensor is used to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router;

[0067] The aggregation router is used to verify the aggregated data set and upload it to the edge blockchain;

[0068] The edge blockchain includes a mimetic hash system for cleaning the verified data set according to the network request to obtain cleaned data, processing the cleaned data using a mimetic hash algorithm to obtain final data, and uploading the final data to the data blockchain;

[0069] The data blockchain is used to store the final data.

[0070] From the above description, it can be seen that the beneficial effects of the present invention are: the converged data set is verified and processed by the convergence routing, and then uploaded to the edge blockchain; the edge blockchain is used to clean the verified data set according to the network request to obtain the cleaned data, and the cleaned data is processed by the mimetic hash algorithm to obtain the final data, and the final data is uploaded to the data blockchain; the final data is stored in the data blockchain, and the data integrity verification based on the mimetic hash technology in the blockchain trusted sensor is combined with the idea of ​​mimetic defense. Dynamic and heterogeneous components are added to the original data integrity verification based on static isomorphism, and a dynamic heterogeneous blockchain sensor data security transmission and integrity verification scheme is constructed, which enhances the security of data integrity verification, thereby ensuring the authenticity of the blockchain data and the reliability of the data source, thereby ensuring the consistency of the blockchain data on and off the chain.

[0071] The blockchain trusted sensor implementation method and system based on mimetic hashing technology described above can be applied to scenarios where consistency of sensor data on and off the chain is required. The following is an explanation of the specific implementation methods:

[0072] In the dynamic heterogeneous redundancy model, the input agent needs to distribute the input sequence to the corresponding (multiple) heterogeneous functional equivalents according to the instructions of the negative feedback controller. The executors in the reconfigurable executor set that are stimulated by the input should, with a high probability, be able to operate normally and independently generate output vectors that meet the given semantics and syntax. The multimodal arbiter, based on the arbitration parameters or the arbitration strategy generated by the algorithm, determines the consistency of the multimodal output vector content and forms an output response sequence. Once an unexpected state is detected, the negative feedback controller is activated. After activation, the negative feedback controller determines, based on the control algorithm generated by the control parameters, whether to send instructions to the output agent to replace (migrate) the "output abnormal" executor, or to instruct the suspected problematic executor to perform online / offline cleaning and recovery operations (including triggering other background processing functions), or to perform a combination of operations such as reorganization, reconstruction, and reconfiguration of the abnormal executor itself based on functional equivalence conditions based on software and hardware components. This activation process is suspended until the output vector inconsistency disappears in the multimodal arbitration link or the occurrence frequency of this situation falls below a given threshold.

[0073] A hash function is a cryptographic algorithm, also known as a hash function or digest function. A hash function is a public function that maps a message M of arbitrary length into a shorter, fixed-length value H(M). H(M) is also called a hash value, hash value, or message digest. It is a one-way cryptographic system—an irreversible mapping from plaintext to ciphertext, involving only encryption and no decryption. Hash features: ① Easy to compress: For input x of arbitrary size, the length of the hash value is very small. In practical applications, the hash value generated by function H is of fixed length. ② Easy to compute: For any given message, it is relatively easy to calculate its hash value. ③ One-way: For a given hash value, it is computationally infeasible to find a solution that is computationally infeasible. In other words, finding the inverse of the hash is difficult. Given a hash function H and a hash value H(M), it is computationally infeasible to derive M. This means that the original input value cannot be deduced from the hash output. This is the foundation of the hash function's security. ④ Collision resistance: An ideal hash function is collision-free, but this is difficult to achieve in practical algorithm design. There are two types of collision resistance: weak collision resistance, which states that for a given message, it is computationally infeasible to discover another message; and strong collision resistance, which states that for any pair of different messages, it is computationally infeasible. ⑤ High sensitivity: This is based on the bit perspective, meaning that a change in 1 bit of input will cause 1 / 2 of the bits to change. Any change in message M will result in a change in the hash value H(M). This means that even a slight difference in the input will result in a different hash output. Therefore, hashing algorithms are a traditional and effective method for verifying data integrity.

[0074] Example 1

[0075] Please refer to Figure 1 、 Figure 4-Figure 6 and Figure 11 , a blockchain trusted sensor implementation method based on mimetic hashing technology in this embodiment includes the following steps:

[0076] S1. Deploy the data blockchain to the cloud side, deploy the edge blockchain to the edge side, and deploy the blockchain trusted sensor and aggregation router to the end side, such as Figure 4 As shown, Figure 4 S1 to S4 represent different sensors. In different scenarios, multiple sensors may collect the same data at the same time. That is, multiple sensors have the same function. For example, in dual-carbon applications, direct carbon emission data is collected by multiple sensors deployed in emission equipment, then concentrated in the blockchain trusted sensor and forwarded to the aggregation router.

[0077] In an optional embodiment, as Figure 4 As shown, the data blockchain and the third-party cloud computing service purchased by the user are deployed to the cloud side. The data blockchain is used to store all data hashes in the business scenario, and the edge blockchain is deployed to the edge side. The edge side is composed of a service sub-chain built by an untrusted edge node close to the source data collected by the sensor, where multiple parallel sub-chains can be constructed according to actual business needs, and the blockchain trusted sensor and the aggregation router are deployed to the end side, that is, a master-slave collaborative chain architecture design is adopted.

[0078] S2, obtaining multiple heterogeneous operating systems, multiple heterogeneous execution environments, and multiple heterogeneous hash algorithms;

[0079] S3. Form a plurality of heterogeneous executables according to the plurality of heterogeneous operating systems, the plurality of heterogeneous execution environments, and the plurality of heterogeneous hash algorithms, and generate a heterogeneous executable pool according to the plurality of heterogeneous executables.

[0080] The full name of the heterogeneous executive is functionally equivalent heterogeneous executive, that is, an executive with the same function but completely different structure, which is equivalent to a complex hash algorithm. Assuming there are w heterogeneous operating systems, m heterogeneous hash algorithms, and n heterogeneous execution environments, w×m×n heterogeneous executives can be formed. If j target heterogeneous executives are scheduled to work each time, then there are By combining these combinations, the probability of an attacker attempting to compromise the system by attacking the hash algorithm is greatly reduced. In other words, the complexity and security of the system increase with the capacity of the heterogeneous executor pool. Changing the hash algorithm's operating environment essentially involves compiling and executing the same hash algorithm in different high-level languages ​​on different operating systems. The hash algorithm and scheduling algorithm in the system should be stored independently in the permissioned blockchain system to ensure their immutability and anonymity.

[0081] S4. Use blockchain trusted sensors to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router;

[0082] In an optional embodiment, the hash algorithm is pre-burned into the blockchain trusted chip of the blockchain trusted sensor; the processed source data is forwarded to the aggregation router via a dedicated network, such as Figure 4 shown.

[0083] S5. Aggregate the processed source data using the aggregation route to obtain a data set, verify the data set, and upload it to the edge blockchain;

[0084] S6. Using the mimetic hash system in the edge blockchain (i.e. Figure 4 The mimetic hash server in the cleans the verified data set according to the network request, obtains the cleaned data, and completes the removal of dirty data;

[0085] The cache function of the edge blockchain is similar to that of the Redis database. The data cached by the edge blockchain can provide query services for users during the business cycle. In an optional implementation, Figure 5 As shown, it also includes: using the edge blockchain to regularly overwrite historical data according to its own storage space upper limit.

[0086] S7, using the mimetic hash system to process the cleaned data according to the mimetic hash algorithm to obtain the final data, and uploading the final data to the data blockchain for storage, such as Figure 4 and Figure 5 As shown, specifically including:

[0087] S71, using the mimetic hash system to distribute the network request to multiple target heterogeneous executors in the heterogeneous executor pool of the mimetic hash system, such as Figure 8 As shown;

[0088] Specifically, the request distribution module is the real entrance of the network request input by the user, such as Figure 6 As shown, the input proxy plug-in in the request distribution module of the mimetic hash system is used to copy and distribute the network request input by the user to multiple target heterogeneous executors in the heterogeneous executor pool of the mimetic hash system, realizing the prerequisite for dynamic changes of heterogeneous executors. Figure 6 China E n Indicates the nth heterogeneous executable.

[0089] S72: Use multiple target heterogeneous executors in the heterogeneous executor pool to simultaneously execute a hash algorithm on the cleaned data to obtain multiple hash results, and send the multiple hash results to a response redundancy voter of the mimetic hash system;

[0090] S73, using the response redundancy voter to cross-judge the multiple hash results according to the voting algorithm, obtain a decision result, and send the decision result to the central scheduler of the mimetic hash system, such as Figure 6 As shown in FIG, the response redundancy voter refers to the multi-mode decision in the mimicry defense abstract model, which is the real outlet of the server response. It can filter out inconsistent information according to the security level requirements to ensure the consistency of the output results.

[0091] The voting algorithm is the existing majority voting method, that is, the minority obeys the majority.

[0092] S74, using the central scheduler to generate a scheduling strategy as final data according to the arbitration result and the preset execution body scheduling algorithm, and updating the multiple target heterogeneous execution bodies according to the scheduling strategy, such as Figure 6 As shown, when updating multiple target heterogeneous executors, elements can be extracted from the heterogeneous resource pool according to a pre-defined reconstruction and reorganization plan to generate new executors with equivalent functions. Alternatively, some components can be replaced in the existing executor, or resources can be reconfigured by adding or removing components in the current executor, or new algorithms can be loaded into programmable and definable components to change the executor's operating environment, or background tasks can be added or removed from the executor to change its working scenario, etc. Specifically, the following are examples:

[0093] S741, using the central scheduler to generate a scheduling strategy as final data according to the arbitration result and a preset execution body scheduling algorithm;

[0094] The preset executable scheduling algorithm refers to the process of reorganizing, reshuffling, and reconstructing functionally equivalent heterogeneous executables, and uses the fed-back executable error information as a reference.

[0095] S742: Use the central scheduler to send the scheduling policy to the dynamic executor scheduler in the heterogeneous executor pool;

[0096] S743. Use the dynamic executor scheduler (DES) to monitor the status of the heterogeneous executors, update the multiple target heterogeneous executors according to the scheduling strategy, and perform pseudo-heterogeneous scheduling on the heterogeneous executors in the heterogeneous executor pool to further enhance the differences between the executors participating in the same redundancy vote, so that the system finally converges to a stable state.

[0097] S744. Use the dynamic execution body scheduler to receive the decision result sent by the negative feedback control module of the central scheduler, and use an event or timing trigger strategy to clean or roll back the heterogeneous execution body according to the decision result, thereby ensuring the integrity of the execution body.

[0098] In an optional embodiment, the dynamic executor scheduler is used to switch the online / offline status of the heterogeneous executors, thereby reducing the continuous exposure time of the heterogeneous executors and improving the security of the heterogeneous executors.

[0099] S75. Upload the final data to the data blockchain for storage.

[0100] In an optional embodiment, the method further includes: S8, using a monitoring module in the mimetic hash system to monitor the blockchain trusted sensor and the network status, obtaining monitoring results, and generating scheduling parameters based on the monitoring results, specifically including:

[0101] S81. Use the monitoring module in the mimetic hash system to monitor the energy state, data consistency state, and online state of the blockchain trusted sensor, and monitor the network traffic state, network transmission state, and network security state to obtain monitoring results.

[0102] Among them, there are two main types of energy conversion for blockchain trusted sensors: one is continuous power supply in a balanced state, and the other is battery power supply in a uniformly declining state. This can be used to monitor the energy status of blockchain trusted sensors; the data before and after the blockchain trusted sensor should be regular, so that its data consistency status before and after can be monitored; by monitoring the online\offline status of the blockchain trusted sensor, the security of the entire system can be controlled.

[0103] S82. Generate scheduling parameters according to the monitoring results.

[0104] like Figure 11 As shown, Figure 11 The paper shows that the mimetic hash technology system is extracted from the blockchain trusted sensor design based on mimetic hash technology, which consists of five layers: the first layer from the outermost layer to the innermost layer includes hash algorithm, mimetic defense technology, identity authentication technology, data processing technology and channel transmission technology; the second layer is the core of mimetic hash technology, including functionally equivalent heterogeneous executors, request distribution module, response redundancy voter, central scheduler, dynamic executor scheduler and monitoring module; the third, fourth and fifth layers are the basis for the operation of blockchain trusted sensors.

[0105] Example 2

[0106] Please refer to Figure 2 、 Figure 3 、 Figure 7-10A system for implementing the method described in Example 1 of this embodiment includes a blockchain trusted sensor, a converged router, an edge blockchain, and a data blockchain:

[0107] The blockchain trusted sensor is used to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router;

[0108] The aggregation router is used to verify the aggregated data set and upload it to the edge blockchain;

[0109] The edge blockchain includes a mimetic hash system for cleaning the verified data set according to the network request to obtain cleaned data, processing the cleaned data using a mimetic hash algorithm to obtain final data, and uploading the final data to the data blockchain;

[0110] The data blockchain is used to store the final data.

[0111] In an optional embodiment, the blockchain trusted sensor hardware consists of a target sensor, a trusted sensor chip / module, a converged router, and a blockchain Bass platform, and the software can consist of an identity authentication system and a mimetic hash system;

[0112] In an optional embodiment, as Figure 7 As shown, the mimetic hash system includes a request distribution module (i.e. Figure 7 The heterogeneous executor pool is composed of three executor components: heterogeneous operating system, heterogeneous execution environment, and heterogeneous hash algorithm. The components dynamically and randomly form heterogeneous redundant functionally equivalent heterogeneous executors according to the scheduling strategy, including but not limited to heterogeneous operating systems such as Windows, Red Hat, CentOS, and Ubuntu, execution environments such as C, JAVA, Python, GO, C#, and C++, and hash algorithms such as MD5, SH-1, RipeMD160, SH-256, and SH-512.

[0113] like Figure 8 As shown, the request distribution module is the real entrance of the network request. The response redundancy voter votes on multiple responses to the same user request according to a predetermined algorithm to obtain a unified output result and feeds the above result back to the central scheduler. Due to the diversity of scenarios, Figure 8The example shows a scenario where multiple sensors acquire data from the same monitored object, hereinafter referred to as similar sensors. For example, sensor 1, sensor 2, and sensor 3 belong to the same category, and the data they collect should theoretically be consistent. After the sensors collect data, they forward it to the aggregation router (blockchain trusted sensor). The aggregation router sends the three data to different heterogeneous executors online for the next step (i.e., sub-request 1, sub-request 2, and sub-request 3). When the heterogeneous executors return operation feedback, the request distribution module compares the responses and handles any abnormal situations.

[0114] The central scheduler generates and sends a scheduling strategy to the request distribution module according to the scheduling algorithm and feedback information, ensuring that the system has sufficient resources and making the system modules loosely coupled to avoid the phenomenon that the system cannot operate normally due to a single point failure; the negative feedback control module in the central scheduler is responsible for receiving the decision result of the response redundancy voter and transmitting the result to the dynamic executor scheduler. The heterogeneous executor pool uses different constructions to achieve the same function, which greatly increases the dynamics of the system and reduces the probability of common mode vulnerabilities in the system. The monitoring module monitors the blockchain trusted sensors and network status, and generates scheduling parameters based on the monitoring results, such as Figure 10 shown.

[0115] Each module in the mimetic hash system, including the request distribution module, heterogeneous executor pool, central scheduler, response redundancy voter and monitoring module, is designed at the software level, and the final implementation is distributed at various levels of the blockchain trusted sensor system.

[0116] The heterogeneous executor pool includes a dynamic executor scheduler, the main function of which is to manage the operation of heterogeneous executors in the heterogeneous executor pool, monitor the status of heterogeneous executors, policy scheduling, receive exceptions pushed by the central scheduler, handle abnormal executors in a timely manner, and block attack chains that exploit vulnerabilities, backdoors, viruses, and Trojans. The dynamic executor scheduler completes the scheduling work of starting and cleaning heterogeneous executors in the heterogeneous executor pool according to predetermined strategies; and performs detection and cleaning tasks based on the exception information broadcast by the central scheduler. In an optional embodiment, the dynamic executor scheduler can be composed of a monitoring system, an executor, and a distributor, such as Figure 9 shown.

[0117] In an optional embodiment, the mimetic hash system is used to distribute the network request to multiple target heterogeneous executors in a heterogeneous executor pool of the mimetic hash system;

[0118] The multiple target heterogeneous executors in the heterogeneous executor pool are used to simultaneously execute a hash algorithm on the cleaned data to obtain multiple hash results, and send the multiple hash results to the response redundancy voter of the mimetic hash system;

[0119] The response redundancy voter is used to perform cross-decision on the multiple hash results according to a voting algorithm to obtain a decision result, and send the decision result to the central scheduler of the mimetic hash system;

[0120] The central scheduler is configured to generate a scheduling strategy as final data according to the arbitration result and a preset execution body scheduling algorithm, and update the multiple target heterogeneous execution bodies according to the scheduling strategy.

[0121] In an optional embodiment, the monitoring module is used to monitor the blockchain trusted sensor and network status, obtain monitoring results, and generate scheduling parameters based on the monitoring results.

[0122] The central scheduler is configured to send the scheduling policy to the dynamic executor scheduler in the heterogeneous executor pool;

[0123] The dynamic execution body scheduler is used to monitor the status of the heterogeneous execution bodies and update the multiple target heterogeneous execution bodies according to the scheduling strategy.

[0124] In an optional embodiment, the dynamic execution body scheduler is used to receive the decision result sent by the central scheduler, and use an event or timer trigger strategy to clean or roll back the heterogeneous execution body according to the decision result.

[0125] In an optional embodiment, the edge blockchain is also used to periodically overwrite historical data according to its own storage space upper limit.

[0126] like Figure 3 As shown, Figure 3 The system architecture of a blockchain-based trusted sensor based on mimetic hashing technology was demonstrated. This system adds a blockchain layer to the traditional three-tier IoT architecture. The perception layer includes source sensors, a perception layer network, a blockchain-based trusted module / chip, and a request dispatch module. The network layer includes an authentication system that provides identity authentication services to the underlying layers, and a central scheduler that acts as the executor of the mimetic hashing system's scheduling and control. The blockchain layer includes the blockchain Bass platform, which provides one-stop on-chain services, an executor pool (i.e., a heterogeneous executor pool) composed of hash algorithm executor components, and the core policy algorithms supporting the operation of the mimetic hashing system—executor scheduling and mimetic adjudication policies. The application layer encompasses different application forms based on specific scenarios. In one optional implementation, this application form can be a dual-carbon application.

[0127] In summary, the present invention provides a blockchain trusted sensor implementation method and system based on mimetic hash technology, which uses a blockchain trusted sensor to collect source data, and uses a hash algorithm to perform preliminary hash processing on the source data, and forwards the processed source data to the aggregation route; uses the aggregation route to aggregate the processed source data to obtain a data set, and uploads the data set to the edge blockchain after verification processing; uses the mimetic hash system in the edge blockchain to clean the verified data set according to the network request to obtain the cleaned data; uses the mimetic hash system to process the cleaned data according to the mimetic hash algorithm to obtain the final data, and uploads the final data to the data blockchain for storage. The data integrity verification based on mimetic hash technology in the blockchain trusted sensor is combined with the idea of ​​mimetic defense, which is based on the original data integrity verification based on static isomorphism. On the basis of integrity verification, dynamic and heterogeneous components are added to construct a dynamic heterogeneous blockchain sensor data security transmission and integrity verification scheme, which enhances the security of data integrity verification and further ensures the authenticity of blockchain data and the reliability of data sources, thereby ensuring the consistency of blockchain data on and off the chain; at the same time, heterogeneous executor pools, central schedulers and response redundancy voters are used to jointly complete mimetic hash processing, and a dynamic heterogeneous redundant architecture is adopted to apply mimetic camouflage strategies to the dynamic heterogeneous redundant multi-mode arbitration, output agency, input allocation, feedback control and multi-dimensional dynamic reconstruction links of the executor, so that the defense environment has the inherent properties of "uncertainty, lockability, controllability and difficulty in coordination". It can not only provide point-surface fusion defense that is independent of attack behavior and feature information, but also effectively disintegrate the situation of coordinated attack achieved through trial and error or elimination method, thereby ensuring data security.

[0128] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A blockchain trusted sensor implementation method based on mimetic hashing technology, characterized in that: Including steps: Use blockchain trusted sensors to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router; Aggregating the processed source data using the aggregation route to obtain a data set, and uploading the data set to the edge blockchain after verification; Using the mimetic hash system in the edge blockchain to cleanse the verified data set according to the network request to obtain cleansed data; The cleaned data is processed using the mimetic hash system according to the mimetic hash algorithm to obtain final data, and the final data is uploaded to the data blockchain for storage.

2. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 1 is characterized in that: The using the mimetic hash system to process the cleaned data according to the mimetic hash algorithm to obtain final data includes: Distributing the network request to a plurality of target heterogeneous executors in a heterogeneous executor pool of the mimetic hash system using the mimetic hash system; Using multiple target heterogeneous executors in the heterogeneous executor pool to simultaneously execute a hash algorithm on the cleaned data to obtain multiple hash results, and sending the multiple hash results to a response redundancy voter of the mimetic hash system; Using the response redundancy voter to perform cross-decision on the multiple hash results according to a voting algorithm to obtain a decision result, and sending the decision result to the central scheduler of the mimetic hash system; The central scheduler is used to generate a scheduling strategy as final data according to the arbitration result and a preset execution body scheduling algorithm, and the multiple target heterogeneous execution bodies are updated according to the scheduling strategy.

3. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 2 is characterized in that: Also includes: The monitoring module in the mimetic hash system is used to monitor the blockchain trusted sensor and network status, obtain monitoring results, and generate scheduling parameters based on the monitoring results.

4. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 3 is characterized in that: The monitoring module in the mimetic hash system is used to monitor the blockchain trusted sensor and network status, and the monitoring results obtained include: The monitoring module in the mimetic hash system is used to monitor the energy state, data consistency state and online state of the blockchain trusted sensor, and to monitor the network traffic state, network transmission state and network security state to obtain monitoring results.

5. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 1 is characterized in that: Before using blockchain trusted sensors to collect source data, the method further includes: Access to multiple heterogeneous operating systems, multiple heterogeneous execution environments, and multiple heterogeneous hashing algorithms; A plurality of heterogeneous execution bodies are formed according to the plurality of heterogeneous operating systems, the plurality of heterogeneous execution environments and the plurality of heterogeneous hash algorithms, and a heterogeneous execution body pool is generated according to the plurality of heterogeneous execution bodies.

6. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 2 is characterized in that: Updating the plurality of target heterogeneous executables according to the scheduling strategy includes: Using the central scheduler to send the scheduling policy to the dynamic executor scheduler in the heterogeneous executor pool; The dynamic executable scheduler is used to monitor the status of the heterogeneous executables, and the multiple target heterogeneous executables are updated according to the scheduling strategy.

7. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 6 is characterized in that: After updating the plurality of target heterogeneous executables according to the scheduling strategy, the method further includes: The dynamic execution body scheduler is used to receive the decision result sent by the central scheduler, and according to the decision result, an event or timing trigger strategy is used to clean or roll back the heterogeneous execution body.

8. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 1, characterized in that: Before using blockchain trusted sensors to collect source data, the method further includes: The data blockchain is deployed to the cloud side, the edge blockchain is deployed to the edge side, and the blockchain trusted sensor and the aggregation router are deployed to the end side.

9. The method for implementing a blockchain trusted sensor based on mimetic hashing technology according to claim 1, characterized in that: Also includes: The edge blockchain is used to periodically overwrite historical data according to its own storage space upper limit.

10. A system for implementing the method according to any one of claims 1 to 9, characterized in that: Including blockchain trusted sensors, aggregation routing, edge blockchain and data blockchain: The blockchain trusted sensor is used to collect source data, perform preliminary hash processing on the source data using a hash algorithm, and forward the processed source data to the aggregation router; The aggregation router is used to verify the aggregated data set and upload it to the edge blockchain; The edge blockchain includes a mimetic hash system for cleaning the verified data set according to the network request to obtain cleaned data, processing the cleaned data using a mimetic hash algorithm to obtain final data, and uploading the final data to the data blockchain; The data blockchain is used to store the final data.

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