Bidding and tendering data security processing method based on block chain

Abstract

The invention discloses a blockchain-based bidding and tendering data security processing method, which belongs to the technical field of data encryption, and specifically comprises the following steps of: segmenting original data into logic blocks according to a time axis, and generating a dynamic feature code containing a hierarchical relationship by using a current data hash value and a last feature segment of a preorder block through nonlinear fusion; and constructing a three-dimensional verification topology network containing a timestamp longitudinal chain, a content association transverse tree and an environment parameter space matrix. And establishing a dynamic verification channel, activating three-anchor-point association path cross verification when data is called, and generating an integrity proof. A self-destruction mechanism is implanted in verification, and data blocks are subjected to gradient erasure when abnormal conditions occur. And finally, generating a traceability map, dispersing encryption key parameters in multiple domains, and recording a storage domain coordinate hash abstract through a block chain. The method is suitable for high-security electronic bidding and tendering scenes.

Description

Technical Field

[0001] The present invention relates to the field of data encryption technology, and in particular to a method for securely processing bidding data based on blockchain. Background Art

[0002] In today's digital age, bidding activities, as an important way to allocate resources and reach transactions in the market economy, are gradually changing from the traditional offline model to the online model. With the rapid development of information technology, the amount of data generated in the bidding process has exploded, covering sensitive and critical data such as the qualification information, quotation details, and technical solutions of the bidding companies. These data not only relate to the commercial secrets and interests of the participants, but also have a significant impact on the fairness, impartiality and transparency of the entire bidding market. Therefore, ensuring the security of bidding data has become a key issue that needs to be urgently addressed in the development of digital bidding.

[0003] At present, some relevant technologies and methods have been applied in the secure processing of bidding data. Some companies have adopted traditional data encryption technologies, such as symmetric encryption and asymmetric encryption algorithms, to encrypt, store and transmit bidding data to prevent the data from being stolen or tampered with during transmission. Some systems have also introduced access control mechanisms to limit access to bidding data through user identity authentication and authorization management. In addition, blockchain technology has also begun to be used in the secure processing of bidding data due to its decentralized, tamper-proof and traceable characteristics. Some solutions use the distributed ledger of blockchain to record the operation history of bidding data to enhance the credibility and transparency of the data.

[0004] Although traditional data encryption technology can protect the confidentiality of data to a certain extent, its security is gradually challenged in the face of increasingly complex network attacks. Although the access control mechanism can limit the access rights of data, it cannot effectively prevent the illegal operation and data leakage of internal personnel. The existing blockchain-based bidding data security processing solutions often only focus on the recording and tracing of data, lacking an effective verification mechanism for data integrity and authenticity, and are difficult to deal with situations where data is maliciously tampered with or forged. In addition, when data anomalies occur, the existing solutions lack effective emergency processing and data recovery mechanisms, and are unable to protect data security and restore data to normal use in a timely manner. Summary of the invention

[0005] The purpose of the present invention is to provide a blockchain-based bidding data security processing method to solve the following technical problems: Traditional data encryption technology focuses on data recording and tracing, lacks an effective verification mechanism for data integrity and authenticity, and is difficult to deal with situations where data has been maliciously tampered with or forged.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for securely processing bidding data based on blockchain, comprising the following steps: The original data is divided into continuous logical data blocks according to the time axis, and each data block generates a dynamic feature code containing a hierarchical relationship. The dynamic feature code is generated by a nonlinear fusion operation of the current data hash value and the last feature segment of the previous block; Construct a three-dimensional verification topology network, and generate three verification anchor points for each data block: a vertical verification chain marked by a timestamp, a horizontal verification tree associated with data content, and a spatial verification matrix bound to external environment parameters; Establish a dynamic verification channel, and synchronously activate the associated verification paths of the three anchor points when retrieving data, and generate data integrity proof through path cross-verification; A self-destruction trigger mechanism is embedded in the verification process. When an abnormal verification path topology is detected, the abnormal data block is automatically erased by gradient. Generate a data traceability map, encrypt the key parameters of the verification process and store them in multiple independent storage domains, and record the hash summary of the storage domain coordinates through the blockchain node.

[0007] As a further solution of the present invention: the dynamic feature code generation process includes: The data block content is divided into three parts: the leading area, the core area, and the check area. The leading area extracts the last 12-byte feature segment of the preceding data block as the fusion seed. The core area generates a variable-length hash value weighted based on content sensitivity. The check area collects system clock signals and environmental noise parameters to generate random disturbance factors. The feature code is generated through a three-stage fusion algorithm: first, the fusion seed and the front segment of the hash value are subjected to cyclic shift cross operation, and then the operation result and the disturbance factor are superimposed modularly. Finally, the superimposed value is divided into left and right halves to perform mirror reflection recombination to form an irreversible feature code with time and space correlation.

[0008] As a further solution of the present invention: the construction of the three-dimensional verification topology network includes: The vertical verification chain is formed by connecting the feature codes of consecutive data blocks end to end, and each node contains a timestamp check value and a data block length fingerprint; the horizontal verification tree establishes a branch structure according to the data type, and each branch node stores a set of associated hash values ​​for data blocks of the same type; the spatial verification matrix generates a three-dimensional coordinate verification map based on the data storage location. Each coordinate point contains a geographic location hash, a device fingerprint, and an environmental electromagnetic feature. The three are formed into a verification vector through orthogonal projection. The verification paths in the three dimensions must simultaneously meet the topological consistency conditions when accessing data.

[0009] As a further solution of the present invention: the activation process of the dynamic verification channel includes: When a data access request is initiated, the spatiotemporal feature elements in the request parameters are automatically identified, the verification marks of the three nodes before and after the current data block are extracted from the vertical chain, the five most recent operation records of the same type of data are retrieved from the horizontal tree, and a snapshot of the environmental features of the storage device is obtained from the spatial matrix. The three sets of parameters are input into the path verification model, which calculates the deviation between the current request and the normal operation by comparing with the historical operation pattern library. When the deviation exceeds the threshold, enhanced verification is triggered, requiring the provision of continuous feature codes of five adjacent data blocks.

[0010] As a further solution of the present invention: the specific implementation of the gradient erasing process includes: After detecting data anomalies, we first lock the abnormal data block and the three data blocks before and after it, and generate an erasure gradient template: the first gradient performs feature code obfuscation processing on the abnormal block, decomposes the original feature code into eight fragments and randomly permutes their positions; the second gradient performs hash value perturbations on adjacent blocks, and resets the verification association while retaining the integrity of the data content; the third gradient implants misleading marks in the storage domain coordinate records, while retaining an encrypted copy of the real coordinates. The original data can only be restored after passing triple reverse verification.

[0011] As a further solution of the present invention: the process of generating the data traceability map includes: The four-dimensional feature vector of each data operation is recorded, including the operation time value, the hardware fingerprint of the operation terminal, the characteristic waveform of the network environment, and the topological map of the data change trajectory. The feature vector is divided into three dimensions and encrypted separately: the time dimension adopts forward rolling encryption, the space dimension uses a dynamic key bound to the environmental parameters, and the content dimension implements sharding threshold encryption. The encrypted data blocks are dispersedly stored in geographically isolated storage nodes through the back propagation algorithm. Each node only stores an invalidated copy of the data fragment. The complete data needs to be reversely reorganized through the storage path recorded in the blockchain.

[0012] As a further solution of the present invention: the independent storage domain specifically includes: Each storage domain implements a differentiated data protection scheme. The first type of storage domain adopts time-dimension sharding storage, distributing data slices to different physical areas according to operation time; the second type of storage domain implements content-associated storage, forcibly separating logically associated data blocks for storage; the third type of storage domain deploys a decoy data generation system to automatically create data copies with the same characteristics as the real data but with invalid content. The access logs of all storage domains are processed through heterogeneous encryption algorithms to generate unassociated verification tags that are stored in blockchain nodes.

[0013] As a further solution of the present invention: when the same type of topological anomaly is detected in three consecutive verification cycles, the data self-healing program is started. First, the feature template of the normal operation mode is extracted from the historical verification record, and then the abnormal data stream is mirrored and reconstructed. The reconstruction process adopts a double verification strategy: the forward verification calculates the theoretical value according to the feature code generation rule, and the reverse verification infers the reasonable value through the correlation between adjacent data blocks. When the two-way verification results converge, a repair patch is automatically generated and all associated verification paths are updated, while retaining the encrypted image of the original data for audit traceability.

[0014] Beneficial effects of the present invention: The present invention divides the original data according to the time axis and generates a dynamic feature code, which is obtained by nonlinear fusion operation of the current data hash value and the last feature segment of the previous block, which can ensure the uniqueness and non-tamperability of the data, and uses the irreversible feature code with time and space correlation generated by the three-stage fusion algorithm to enhance the complexity and security of the data features. The constructed three-dimensional verification topological network includes a vertical verification chain marked by timestamps, a horizontal verification tree associated with data content, and a spatial verification matrix bound to external environmental parameters. It can verify the data from multiple dimensions to ensure the consistency of data in time, content and environment. The dynamic verification channel synchronously activates the associated verification path of the three anchor points when the data is retrieved, and generates data integrity proof through path cross-verification, which can effectively identify abnormal access requests and improve the security of data access. The implanted self-destruction trigger mechanism implements gradient erasure processing on the abnormal data block when the verification path topological structure is detected to be abnormal, including feature code obfuscation, hash value perturbation and implantation of misleading marks, etc., which can prevent further leakage of data and malicious use. The generated data traceability graph encrypts the key parameters of the verification process and stores them in a decentralized manner. It combines the hash summary of the storage domain coordinates recorded by the blockchain node to achieve data traceability and multi-domain secure storage. At the same time, different independent storage domains adopt differentiated data protection solutions, such as time dimension shard storage, content-related storage, and deployment of bait data generation systems, which enhances the data's anti-attack capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a method for securely processing bidding data based on blockchain, comprising the following steps: The original data is divided into continuous logical data blocks according to the time axis. A dynamic feature code with a hierarchical relationship is generated for each data block, which is obtained by nonlinear fusion operation of the current data hash value and the last feature segment of the previous block. This operation gives the feature code uniqueness and coherence to prevent data tampering and forgery. Construct a three-dimensional verification topology network, and generate three verification anchor points for each data block: the vertical verification chain marked by timestamps, which connects the feature codes of consecutive data blocks end to end, and the nodes contain timestamp check values ​​and data block length fingerprints to ensure the integrity of the time dimension data; the horizontal verification tree associated with data content, which builds a branch structure according to the data type, and the branch nodes store the hash value set associated with the same type of data blocks to verify the logical relationship of the data content; the spatial verification matrix bound to external environmental parameters generates a three-dimensional coordinate verification map based on the data storage location. The coordinate points contain geographic location hash, device fingerprints and environmental electromagnetic characteristics, and form verification vectors through orthogonal projection. When accessing data, the three-dimensional verification paths must meet the topological consistency conditions at the same time. A dynamic verification channel is established to automatically and synchronously activate the three anchor point associated verification paths when data is retrieved. The verification marks of the three nodes before and after the current data block are extracted from the vertical chain, the five most recent operation records of the same type of data are retrieved from the horizontal tree, and the snapshot of the storage device environment characteristics is obtained from the spatial matrix. The input path verification model is compared with the historical operation mode library to calculate the deviation. When the deviation exceeds the threshold, enhanced verification is triggered, requiring the provision of continuous feature codes of five adjacent data blocks to generate data integrity proof. A self-destruct trigger mechanism is implanted in the verification process. When an abnormal topological structure of the verification path is detected, the abnormal data block is automatically subjected to gradient erasure processing. The abnormal data block and its three related data blocks are locked. The first gradient confuses the abnormal block feature code and decomposes it into eight fragments with random position replacement; the second gradient perturbs the hash value of the adjacent blocks, resets the verification association and keeps the data content intact; the third gradient implants misleading marks in the storage domain coordinate record and saves the encrypted copy of the real coordinate at the same time. Triple reverse verification is required to restore the original data. Generate a data traceability map to record the four-dimensional feature vector of each data operation, including the operation time value, the hardware fingerprint of the operation terminal, the characteristic waveform of the network environment, and the topological map of the data change trajectory. Encrypt the feature vector in three dimensions: forward rolling encryption in the time dimension, dynamic keys bound to environmental parameters in the space dimension, and sharding threshold encryption in the content dimension. The encrypted data blocks are dispersedly stored in geographically isolated storage nodes through the back-propagation algorithm. The nodes only store invalid copies of data fragments. The complete data needs to be reversely reorganized through the storage domain coordinate hash summary recorded by the blockchain node to achieve data security storage and traceability.

[0019] In a preferred embodiment of the present invention, the dynamic feature code generation process includes: First, the data block content will be scientifically divided into three parts: the leading area, the core area, and the check area. In the leading area, the 12-byte feature segment at the end of the preceding data block will be accurately extracted and used as the core seed for subsequent fusion operations. This 12-byte feature segment contains the key feature information of the preceding data block, laying the foundation for building the coherence and correlation between data. The core area is responsible for generating a variable-length hash value weighted by content sensitivity. Since the content of bidding data is complex and diverse, and different parts have different sensitivities, the hash value generated by this weighted method can more accurately reflect the characteristics of the core content of the data block and improve the sensitivity of the hash value to changes in data content. The check area collects system clock signals and environmental noise parameters to generate random perturbation factors. The system clock signal reflects the time characteristics of data processing, while the environmental noise parameters reflect the characteristics of the external environment when the data is generated or processed. The random perturbation factor generated by the combination of the two adds additional complexity and randomness to the feature code. Subsequently, the signature code is generated through a sophisticated three-stage fusion algorithm. In the first stage, the fusion seed and the front end of the hash value are subjected to a cyclic shift cross operation. This operation method allows the features of the previous data block to be deeply interwoven with the core content features of the current data block, and initially establishes a close connection in the time dimension and content dimension. In the second stage, the operation result of the first stage is superimposed on the disturbance factor by modular exponentiation. Modular exponentiation has a high degree of complexity. Superimposing the operation result with the disturbance factor further enhances the unpredictability of the signature code, making it difficult to crack or forge. In the last stage, the superimposed value is divided into left and right halves for mirror reflection and reorganization. After this operation, an irreversible signature code with time and space correlation is finally formed. This irreversibility ensures that once the signature code is generated, the original data cannot be reversed by conventional means, which greatly improves the security of the data. In another preferred embodiment of the present invention, the construction of the three-dimensional verification topology network includes: The vertical verification chain is naturally formed by connecting the characteristic codes of consecutive data blocks end to end. Each node carefully contains the timestamp check value and the data block length fingerprint. The timestamp check value accurately records the time point when the data block is generated or updated, which not only helps to strictly verify the order and continuity of the data in the time dimension, but also provides key time clues for subsequent data auditing and tracing. The data block length fingerprint identifies the data block from the perspective of data volume. Once the data block length changes abnormally, it can be quickly detected, effectively ensuring the integrity of the data in the time dimension. The horizontal verification tree establishes a branch structure according to the data type. This structural design meets the needs of classified management of bidding data. Each branch node stores a set of associated hash values ​​for data blocks of the same type. In this way, when it is necessary to verify the logical relationship between a certain data block and other data blocks of the same type, the relevant hash value can be quickly obtained from the corresponding branch node for comparison. For example, when verifying the consistency of the same type of qualification certificate data in the bidding documents, the horizontal verification tree can play an efficient role and verify the logical relationship of the data content. The spatial verification matrix generates a three-dimensional coordinate verification map based on the data storage location. Each coordinate point contains a geographic location hash, a device fingerprint, and an environmental electromagnetic feature. The geographic location hash accurately identifies the geographic location information of the data storage, the device fingerprint records the unique hardware features of the storage device, and the environmental electromagnetic feature reflects the electromagnetic characteristics of the data storage environment. The three are formed into a verification vector through orthogonal projection. This multi-factor fusion verification method comprehensively verifies the data from the spatial and environmental dimensions. When accessing data, the verification paths of the three dimensions must simultaneously meet the topological consistency conditions. Only when the verification of the vertical, horizontal, and spatial dimensions is passed, the legitimacy of the data access request is recognized, and data security is fully guaranteed. In another preferred embodiment of the present invention, the activation process of the dynamic verification channel includes: When initiating a data access request, identify the spatiotemporal feature elements in the request parameters. These spatiotemporal feature elements contain key information such as the time when the request was initiated and the geographical location of the initiating terminal, providing basic clues for subsequent verification. Extract the verification marks of the three nodes before and after the current data block from the vertical chain. These verification marks carry the key verification information of the data block in the time dimension, which helps to judge the rationality of the current data block in the time series. Retrieve the five most recent operation records of the same type of data from the horizontal tree. By analyzing the recent operation status of the same type of data, it can better judge whether the data operation of the current request conforms to the normal operation mode of this type of data. Obtain a snapshot of the environmental characteristics of the storage device from the spatial matrix, which can ensure the consistency of the current data access environment and the data storage environment. Next, these three sets of parameters are input into a carefully constructed path verification model. The model pre-stores a rich library of historical operation modes. By deeply comparing the current request parameters with the historical operation modes, it accurately calculates the deviation between the current request and the normal operation. When the deviation exceeds the pre-set threshold, it means that there is an abnormal risk in the current data access request, and enhanced verification is immediately triggered. Enhanced verification requires the provision of continuous feature codes of five adjacent data blocks. Through further verification of the feature codes of adjacent data blocks, the legitimacy of the data access request is reconfirmed from the perspective of data consistency and correlation, thereby generating a more reliable data integrity certificate, effectively preventing illegal data access, and effectively ensuring the security of bidding data.

[0020] In another preferred embodiment of the present invention, the specific implementation of the gradient erasing process includes: When data anomalies are detected, the abnormal data block and the three data blocks before and after it will be accurately locked. The reason for choosing to associate the three data blocks before and after is that there is often a close logical connection between the data. The abnormal data may have an impact on the surrounding data. Expanding the locking range helps to comprehensively deal with potential risks.

[0021] After locking the data block, an erase gradient template is immediately generated. The first gradient mainly implements feature code obfuscation processing for abnormal blocks. Specifically, the original feature code is carefully decomposed into eight fragments, and then the positions of these fragments are replaced using a random algorithm. This operation causes the feature code of the abnormal block to completely lose its original structure. Even if the attacker obtains these fragments, it is difficult to restore the original feature code, which greatly increases the difficulty of data cracking. The second gradient focuses on adjacent blocks. Hash value perturbation operations are performed on adjacent blocks, and in this process, the integrity of the data content is cleverly preserved. The hash value is adjusted through a specific algorithm to reset the verification association between the adjacent blocks and the abnormal blocks. In this way, the impact of the abnormal blocks is effectively isolated, preventing the spread of abnormal data in the associated data, while ensuring that the availability of normal data is not affected.

[0022] The third gradient is to implant misleading marks in the storage domain coordinate records. Generate seemingly reasonable but actually wrong coordinate information to interfere with potential attackers' judgment of the data storage location. At the same time, the real coordinates are encrypted and a copy is saved. Only after strict triple reverse verification and confirmation that the operation is legal can the real coordinates be obtained and used to restore the original data. This layered gradient erasure processing method adds multiple protection barriers to data security, effectively preventing data leakage and malicious use. In another preferred embodiment of the present invention, the process of generating the data traceability graph includes: The four-dimensional feature vector of each data operation is recorded in detail, in which the operation time value is accurate to an extremely fine time scale, which can accurately reflect the moment when the data operation occurs, and provide a high-precision basis for tracing the time dimension. The hardware fingerprint of the operation terminal records the unique hardware characteristics of the device that performs the data operation. Whether it is the CPU model of the computer, the motherboard serial number, or the IMEI code of the mobile device, they are all included in the record range, which helps to determine the initiator of the data operation. The network environment characteristic waveform captures the electromagnetic characteristics of the network environment during data transmission, such as changes in signal strength, frequency, etc., providing clues for analyzing the data transmission path and environment. The data change trajectory topology diagram intuitively shows the change path and logical relationship of the data during the operation process, such as the order and mutual correlation of operations such as data modification, deletion, and addition. After recording these feature vectors, they are divided into three dimensions for encryption processing. In the time dimension, forward rolling encryption is adopted. This encryption method continuously updates the encryption key over time. After each data operation, a new key is generated based on the new time factor to encrypt the subsequent data, so that the encryption status of the data in the time dimension is different at different time points, which enhances the security of the data. The spatial dimension uses dynamic keys bound to environmental parameters, and incorporates the environmental parameters of the data storage location, such as geographical location, electromagnetic interference of surrounding equipment, etc. into the key generation process. When the environmental parameters change, the key also changes accordingly, further ensuring the confidentiality of the spatial dimension data. The content dimension implements fragmentation threshold encryption, which divides the data content into multiple fragments, sets different encryption thresholds for each fragment, and can only decrypt the fragment data when the corresponding threshold conditions are met, which greatly increases the difficulty of cracking the data content. The encrypted data blocks are stored in geographically isolated storage nodes through the back-propagation algorithm. These storage nodes are distributed in different geographical locations and are physically isolated from each other, which reduces the risk of data leakage caused by attacks on a single storage node. Each node only stores invalidated copies of data fragments, which cannot be directly restored to complete data. Only by reverse reorganization through the storage path recorded in the blockchain can the data fragments scattered in various nodes be reassembled into complete data, realizing secure storage and efficient traceability of data. In another preferred embodiment of the present invention, the independent storage domain specifically includes: Each storage domain implements a differentiated data protection solution. The first type of storage domain adopts a time-dimension sharding storage strategy. It slices the data according to the operation time, and then disperses these slices to different physical areas. For example, the data slices generated in the morning are stored in the storage device in area A, and the data slices generated in the afternoon are stored in the storage device in area B which is farther away. This method disperses the data in both time and space. Even if the storage device in a certain physical area fails or is attacked, it will only affect the data slices in the corresponding time period, and will not cause the overall data to be lost or leaked. The second type of storage domain implements content-associated storage. This method will force the separation of logically associated data blocks. For example, in bidding data, although the qualification documents and quotation documents of bidding companies are logically associated, they will be stored in different storage areas. In this way, when a data block is tampered with or leaked for some reason, the data blocks associated with it can still remain safe, avoiding the chain risk caused by data association. The third type of storage domain deploys a decoy data generation system. This automatically creates a data copy with the same characteristics as the real data but with invalid content. These decoy data look exactly the same as the real data, whether it is the data format, size or feature code, but the actual content is invalid. When an attacker tries to obtain data, they are likely to be misled by these decoy data, which consumes their attack resources and time, thereby protecting the security of the real data. In addition, the access logs of all storage domains are processed by heterogeneous encryption algorithms. Heterogeneous encryption algorithms use a combination of multiple different encryption methods to generate unassociated verification tags and store them in blockchain nodes. This makes it difficult for attackers to obtain data access patterns or crack storage domain information by analyzing access logs, further improving the security of independent storage domains.

[0023] In another preferred embodiment of the present invention, when the same type of topological anomaly is detected in three consecutive verification cycles, the data self-healing program is quickly started. First, the feature template of the normal operation mode is extracted from the historical verification records. These historical records store various feature information in the past data operation process in detail. The system analyzes and selects typical features in the normal operation mode, constructs a feature template, and provides a reference standard for subsequent data reconstruction. Then, the abnormal data stream is reconstructed by mirroring. The reconstruction process adopts a double verification strategy. The forward verification calculates the theoretical value according to the feature code generation rules. The system forward derives the feature code of the abnormal data block based on the previously set dynamic feature code generation rules to obtain the feature code value that should be theoretically present. The reverse verification reversely infers the reasonable value through the correlation of adjacent data blocks. Since there is a close correlation between the data, the possible reasonable value of the abnormal data block is reversely inferred by analyzing the characteristics and logical relationship of adjacent normal data blocks. When the two-way verification results converge, that is, the forward inference value and the reverse inference value tend to be consistent, a repair patch is automatically generated. This repair patch can accurately repair the erroneous part of the abnormal data block and restore it to normal state. At the same time, all associated verification paths are updated to ensure the consistency and accuracy of the entire data verification system. In addition, in order to meet the needs of subsequent audit tracing, the encrypted image of the original data is retained, which can be retrieved for review at any time when needed, providing strong support for data security management.

[0024] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for securely processing bidding data based on blockchain, characterized in that: The following steps are involved: The original data is divided into continuous logical data blocks according to the time axis, and each data block generates a dynamic feature code containing a hierarchical relationship. The dynamic feature code is generated by a nonlinear fusion operation of the current data hash value and the last feature segment of the previous block; Construct a three-dimensional verification topology network, and generate three verification anchor points for each data block: a vertical verification chain marked by a timestamp, a horizontal verification tree associated with data content, and a spatial verification matrix bound to external environment parameters; Establish a dynamic verification channel, and synchronously activate the associated verification paths of the three anchor points when retrieving data, and generate data integrity proof through path cross-verification; A self-destruction trigger mechanism is embedded in the verification process. When an abnormal verification path topology is detected, the abnormal data block is automatically erased by gradient. Generate a data traceability map, encrypt the key parameters of the verification process and store them in multiple independent storage domains, and record the hash summary of the storage domain coordinates through the blockchain node.

2. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The dynamic feature code generation process includes: The data block content is divided into three parts: the leading area, the core area, and the check area. The leading area extracts the last 12-byte feature segment of the preceding data block as the fusion seed. The core area generates a variable-length hash value weighted based on content sensitivity. The check area collects system clock signals and environmental noise parameters to generate random disturbance factors. The feature code is generated through a three-stage fusion algorithm: first, the fusion seed and the front segment of the hash value are subjected to cyclic shift cross operation, and then the operation result and the disturbance factor are superimposed modularly. Finally, the superimposed value is divided into left and right halves to perform mirror reflection recombination to form an irreversible feature code with time and space correlation.

3. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The construction of the three-dimensional verification topology network includes: The vertical verification chain is formed by connecting the feature codes of consecutive data blocks end to end, and each node contains a timestamp check value and a data block length fingerprint; the horizontal verification tree establishes a branch structure according to the data type, and each branch node stores a set of associated hash values ​​for data blocks of the same type; the spatial verification matrix generates a three-dimensional coordinate verification map based on the data storage location. Each coordinate point contains a geographic location hash, a device fingerprint, and an environmental electromagnetic feature. The three are formed into a verification vector through orthogonal projection. The verification paths in the three dimensions must simultaneously meet the topological consistency conditions when accessing data.

4. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The activation process of the dynamic verification channel includes: When a data access request is initiated, the spatiotemporal feature elements in the request parameters are automatically identified, the verification marks of the three nodes before and after the current data block are extracted from the vertical chain, the five most recent operation records of the same type of data are retrieved from the horizontal tree, and a snapshot of the environmental features of the storage device is obtained from the spatial matrix. The three sets of parameters are input into the path verification model, which calculates the deviation between the current request and the normal operation by comparing with the historical operation pattern library. When the deviation exceeds the threshold, enhanced verification is triggered, requiring the provision of continuous feature codes of five adjacent data blocks.

5. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The specific implementation of the gradient erasing process includes: After detecting data anomalies, we first lock the abnormal data block and the three data blocks before and after it, and generate an erasure gradient template: the first gradient performs feature code obfuscation processing on the abnormal block, decomposes the original feature code into eight fragments and randomly permutes their positions; the second gradient performs hash value perturbations on adjacent blocks, and resets the verification association while retaining the integrity of the data content; the third gradient implants misleading marks in the storage domain coordinate records, while retaining an encrypted copy of the real coordinates. The original data can only be restored after passing triple reverse verification.

6. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The generation process of the data traceability graph includes: The four-dimensional feature vector of each data operation is recorded, including the operation time value, the hardware fingerprint of the operation terminal, the characteristic waveform of the network environment, and the topological map of the data change trajectory. The feature vector is divided into three dimensions and encrypted separately: the time dimension adopts forward rolling encryption, the space dimension uses a dynamic key bound to the environmental parameters, and the content dimension implements sharding threshold encryption. The encrypted data blocks are dispersedly stored in geographically isolated storage nodes through the back propagation algorithm. Each node only stores an invalidated copy of the data fragment. The complete data needs to be reversely reorganized through the storage path recorded in the blockchain.

7. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: The independent storage domain specifically includes: Each storage domain implements a differentiated data protection scheme. The first type of storage domain adopts time-dimension sharding storage, distributing data slices to different physical areas according to operation time; the second type of storage domain implements content-associated storage, forcibly separating logically associated data blocks for storage; the third type of storage domain deploys a decoy data generation system to automatically create data copies with the same characteristics as the real data but with invalid content. The access logs of all storage domains are processed through heterogeneous encryption algorithms to generate unassociated verification tags that are stored in blockchain nodes.

8. According to a blockchain-based bidding data security processing method according to claim 1, it is characterized in that: When the same type of topological anomaly is detected in three consecutive verification cycles, the data self-healing program is started. First, the feature template of the normal operation mode is extracted from the historical verification records, and then the abnormal data stream is mirrored and reconstructed. The reconstruction process adopts a double verification strategy: the forward verification calculates the theoretical value according to the feature code generation rule, and the reverse verification infers the reasonable value through the correlation of adjacent data blocks. When the two-way verification results converge, a repair patch is automatically generated and all associated verification paths are updated, while the encrypted image of the original data is retained for audit traceability.

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