Real estate right trusted transaction verification method based on intelligent contract business rule

Abstract

The invention relates to the technical field of transaction verification, and discloses a real estate right credible transaction verification method based on an intelligent contract business rule, which comprises the following steps: analyzing a transaction request to extract a real estate identifier and a rule feature code set divided into rigid blocking and flexible compensation masks, obtaining a right state vector mapping a real-time legal state according to the real estate identifier, calculating an XOR result of the right state vector and the rule feature code set to extract a residual vector, and calculating a bitwise AND result of the residual vector and the rigid blocking mask; if the result is zero and the residual error is not zero, a conditional authority instruction containing risk hedging parameters is generated according to the residual error vector index preset mapping table. According to the exclusive-or residual error extraction and double-layer mask projection mechanism, atomization accurate judgment of the non-binary transaction state is achieved on the premise that complex control flow is not introduced, and the risk hedging accuracy of the non-binary transaction state is improved. And the certainty and execution efficiency of verification logic are improved.

Description

Technical Field

[0001] This invention relates to a method for verifying trusted transactions of real estate rights based on smart contract business rules, belonging to the field of transaction verification technology. Background Technology

[0002] In current distributed ledger and blockchain transaction architectures, smart contracts construct decentralized asset rights transfer and authorization verification systems. These systems involve multi-party rights confirmation for high-value asset transactions, include specific business logic computer protocols, and automatically trigger preset code segments upon receiving transaction instructions. They read on-chain states or call external data interfaces to determine if the transaction request meets current compliance requirements, achieving automated rights confirmation and settlement without manual intervention. As transaction scenarios extend to high-frequency, multi-dimensional, and complex regulatory business environments, traditional technical architectures, which directly compile business rules into contract code, reveal system bottlenecks in addressing dynamically changing compliance needs. Existing technologies hardcode specific business judgment conditions such as tax thresholds, entity qualifications, or asset status into the smart contract execution logic using nested conditional statements. This highly coupled design between logic and rules results in massive contract code size and computational resource consumption that increases linearly with rule complexity. This restricts the system's responsiveness to changes in external policies or business rules. Minor adjustments to external regulatory rules require the system operator to recompile, audit, and deploy the entire smart contract, incurring high time and economic costs and introducing data security risks due to contract migration.

[0003] Besides its rigid architecture, existing technologies have limitations in the depth and flexibility of transaction verification logic. For example, Chinese invention patent application CN119228537A discloses a transaction method and system based on blockchain technology. The solution processes transaction requests through smart contracts, automatically matches counterparties that meet price and address conditions, and records the data into the blockchain after confirmation. The solution uses blockchain technology to solve the problems of transaction transparency and immutability. However, the core logic remains at the level of matching based on static field information. When faced with complex real-time legal status verification of real estate transactions, such as instantaneous seizure and objection registration, the solution lacks a dynamic mapping mechanism and relies solely on binary judgment based on fixed contract terms. When faced with the lack of non-critical data, such as the absence of non-blocking tax certificates, the linear logic cannot distinguish between fatal defects and compensable flaws, and can only mechanically execute rigid blocking. The lack of a gray-scale decision-making verification mechanism reduces the business throughput and resilience of the system in actual complex engineering environments.

[0004] Therefore, the technical problem to be solved by this invention is how to construct a method that completely decouples complex business verification rules from the underlying execution logic, ensures strict time synchronization of multi-source heterogeneous data and atomicity of the verification process, and achieves efficient and deterministic verification of dynamic business rules using low-cost computing methods. Summary of the Invention

[0005] To address the problems mentioned in the background section, the technical solution of this invention is as follows: A method for verifying trusted transactions of real estate rights based on smart contract business rules, the method comprising the following steps: Step 101: Receive transaction verification request, parse transaction verification request to extract real estate unique identifier and corresponding rule feature code set. The rule feature code set is divided into non-overlapping rigid blocking mask and flexible compensation mask in binary bit field. Step 102: Call the oracle interface based on the unique identifier of the real estate to obtain the rights status vector under the current time window. The rights status vector is a binary bitmap that maps the real estate's real-time legal status. Step 103: In the smart contract execution environment, perform atomic logic adjudication on the equity state vector. The atomic logic adjudication includes: calculating the XOR logical operation result of the equity state vector and the rule feature code set, and extracting the residual vector representing the difference bits between the current state and the target rule; calculating the bitwise AND logical operation result of the residual vector and the rigid blocking mask; if the bitwise AND logical operation result is non-zero, generate a transaction blocking instruction; if the bitwise AND logical operation result is zero and the residual vector is non-zero, index the pre-set bit and amount mapping table in the smart contract according to the bit order of the bits in the residual vector, and generate a conditional transaction permission instruction containing risk hedging parameters; if the bitwise AND logical operation result is zero and the residual vector is zero, generate a transaction pass instruction.

[0006] Preferably, step 102 includes: defining a holographic state word structure, which divides the binary data space into several non-overlapping rigid functional bit fields, which are used to map the property rights attribute status, the qualification attribute status of the transaction initiator, and the compliance attribute status of the transaction environment, respectively; receiving the holographic state word constructed by the oracle node as the equity state vector, which is generated by the oracle node in parallel aggregating feedback data from various heterogeneous authoritative data sources within the same time slice and filling it according to the rigid functional bit field structure; and constructing the rule feature code set into a holographic rule mask corresponding to the holographic state word structure to complete the joint verification of cross-domain business rules within a single instruction cycle.

[0007] Preferably, the equity state vector includes a business value vector and a confidence vector that are independent of each other; before step 103, a data validity gating step is also included: obtaining the business value vector and the confidence vector respectively, wherein each bit in the confidence vector is used to characterize the validity of the data source of the corresponding bit in the business value vector at the time of generation; calculating the bitwise AND result of the rule feature code set and the confidence vector; determining whether the bitwise AND result is completely consistent with the rule feature code set; and triggering the step of calculating the XOR logical operation result of the equity state vector and the rule feature code set only if the determination result is consistent.

[0008] Preferably, the step of generating a conditional trading permission instruction containing risk hedging parameters by indexing a pre-set bit-to-amount mapping table in the smart contract based on the bit order of the residual vector includes: extracting the position indices of all binary bits with true values ​​in the residual vector; traversing the position indices and obtaining the unit risk compensation amount corresponding to each position index from the bit-to-amount mapping table; and calculating the total margin amount in the risk hedging parameters according to the following formula. : ,in, For the residual vector, It is a positional index. This represents the total bit width of the residual vector. For bitwise AND operator, For the corresponding number in the bit-to-amount mapping table The unit risk compensation amount; the calculated total margin amount is encapsulated into a conditional trading permission instruction.

[0009] Preferably, the method further includes a dynamic obfuscation step for verification data based on transaction entropy: extracting the transaction hash value of the transaction verification request; calculating dynamic displacement parameters based on the transaction hash value; confirming that both the rule feature code set and the equity state vector have undergone homomorphic bit order permutation processing based on the dynamic displacement parameters before performing the step of calculating the XOR logical operation result of the equity state vector and the rule feature code set; and directly performing the logical operation of the rule feature code set and the equity state vector while maintaining the bit order permutation state.

[0010] Preferably, the method further includes a rule integrity verification step: maintaining a global hash digest of the currently effective rule set published by the rule maker in the smart contract's storage area; extracting the rule version anchor point submitted along with the rule feature code set from the transaction verification request; performing a hash comparison operation to determine whether the rule version anchor point is consistent with the global hash digest; triggering step 103 only if consistent; if inconsistent, determining that the rule parameters of the transaction verification request are invalid and terminating the verification.

[0011] Preferably, step 101, which involves parsing the transaction verification request to extract the unique identifier of the real estate and the corresponding set of rule feature codes, is replaced by a rule-based deterministic addressing step based on state invariants. Specifically, this includes: pre-setting an attribute rule mapping table in the smart contract, which defines the correspondence between the inherent attribute codes of the real estate and the set of rule feature codes; performing a bitmask extraction operation on the equity state vector to parse out the type attribute bit field values ​​representing the inherent attributes of the real estate; using the type attribute bit field values ​​as an index to address and extract the corresponding target rule feature code set in the attribute rule mapping table; and using the target rule feature code set as a unique and valid logical mask for subsequent logical operations.

[0012] Preferably, the holographic status word structure includes a high-order segment for mapping the physical attributes of the real estate, a middle-order segment for mapping the attributes of the buyer, and a low-order segment for mapping the attributes of the transaction environment. The steps for the oracle node to perform off-chain atomic aggregation include: sending status query requests to multiple heterogeneous data sources; if any data source responds with a timeout, then filling the corresponding bit field of the holographic status word with a preset invalid status code; if all data sources respond successfully, then concatenating the individual status codes according to the holographic status word structure to generate a unique holographic status word.

[0013] Preferably, the steps for generating a transaction blocking instruction include: extracting the bit sequence of the non-zero bits in the result of a bitwise AND logical operation; retrieving the corresponding violation type description from a preset error code table based on the bit sequence; generating a transaction rejection receipt containing the violation type description; and writing the transaction rejection receipt into the transaction log area of ​​the blockchain for auditing.

[0014] Preferably, the transaction verification request also includes a timestamp parameter; the method also includes: verifying whether the difference between the timestamp parameter and the current block timestamp is within a preset valid time window; only when the difference is within the valid time window, step 102 is executed; the entire process of atomic logic adjudication is completed within a single smart contract transaction and does not involve cross-block state storage operations.

[0015] Compared with the prior art, the beneficial effects of the present invention are: 1. In the smart contract business rules, a rule feature code and state verification bitmap mapping mechanism is constructed. The complex natural language rules of the transaction verification process are transformed into standardized binary masks, which are directly carried by the transaction instructions to the smart contract execution environment. The smart contract uses pre-set bit logic operators to map the transaction instructions carrying the rule feature code with the off-chain authoritative data source to generate a rights and interests state vector and perform bit-by-bit logic matching operations. The computational complexity, which originally increased linearly with the number of business rule entries, is collapsed into a constant single bit operation. This achieves complete decoupling between the verification logic and the business rules, so that the system can update the off-chain configuration table to adapt to frequently changing external business rules without redeploying the contract code. This ensures deterministic and low-latency response of the transaction verification process in a computing resource-constrained environment.

[0016] 2. Utilizing a holographic state word segmentation and aggregation mechanism and a single-instruction adjudication mechanism, off-chain oracle nodes pull heterogeneous data from different administrative or financial systems in parallel, compress and fill it into a unique binary holographic state word according to a preset rigid functional bit field structure, and the smart contract receives the holographic state word synchronously within the receiving time window. A one-time bitwise AND operation is performed with the holographic rule mask to lock the consistency of all cross-domain data at the verification time, eliminating state preemption or logical vulnerabilities caused by differences in response delays from distributed data sources. By utilizing the parallel characteristics of bitwise operations, a joint verification of multi-dimensional compliance is completed within a single instruction cycle, ensuring the atomicity and rigor of the verification conclusion.

[0017] 3. Construct a residual mask extraction conditional verification logic. When the main verification logic does not fully match, trigger an XOR operation to extract the residual vector representing the state difference. Perform a bitwise comparison with the preset rigid blocking mask and flexible compensation mask to identify non-critical state missingness that belongs to the compensable category. Based on the residual vector position distribution, automatically map and generate a conditional pass instruction containing risk hedging parameters. The system obtains the ability to handle flexible business scenarios without introducing complex branch control code, ensuring the core compliance bottom line while avoiding rigid blocking of transactions due to secondary data missingness, and improving the system throughput and business adaptability in complex transaction environments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the transaction verification process that integrates rigid blocking and flexible compensation mechanisms according to the present invention. Figure 2 This is a line graph showing the test results of the response latency and fluctuation characteristics of the multi-source heterogeneous data service in this invention. Figure 3 This is a schematic diagram of the timing of cross-domain data parallel interaction based on holographic status word aggregation according to the present invention. Detailed Implementation

[0019] The present invention will be described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention.

[0020] This invention discloses a method for verifying trusted transactions of real estate rights based on smart contract business rules. It transforms complex legal compliance verification into CPU instruction-level bitwise operations through bitmap mapping technology, decoupling the verification logic from the business rules. During the system's initialization phase, a standardized mapping protocol is established between rule feature codes and rights status vectors. The protocol defines a fixed-length binary data space, such as 256 bits, logically divided into non-overlapping rigid functional bit fields. These fields are used to map real estate property rights attributes such as mortgage and seizure status, the transaction initiator's qualification attributes such as purchase restriction eligibility, and the compliance attributes of the transaction environment such as tax payment status. Specific business rules are encoded as one or more specific bits within this space, forming a set of rule feature codes. Real-time legal status is mapped as binary status codes at corresponding positions, forming a rights status vector. The smart contract is configured with general bit logic operators AND, OR, and XOR. Based on the input set of rule feature codes as a logic mask, bitwise logic matching operations are performed on the rights status vector obtained from the authoritative data source. The single operation result constitutes the sole basis for generating transaction permission instructions. When external business rules change, only the off-chain rule configuration or transaction request parameters need to be updated, without redeploying the on-chain contract code.

[0021] To address the problem of atomicity breaking in real estate rights transaction verification caused by asynchronous processing of multi-source heterogeneous data, this invention implements a segmented aggregation of holographic state words and a single-instruction adjudication procedure. This requires oracle nodes to trigger a strictly controlled synchronization time window upon receiving a transaction verification request containing the unique identifier of the real estate. If set to 500ms, within this window, nodes concurrently send status query commands to heterogeneous authoritative data sources such as real estate registration centers, tax bureaus, and bank credit reporting systems. The oracle node temporarily stores the individual status codes returned by each data source in a buffer and, according to the preset rigid function bit field definition, fills these status codes bit-by-bit into a 256-bit unsigned integer variable, generating a unique holographic status word as the equity status vector for the current time slice. If a critical data source fails to respond at the end, the corresponding bit field is filled with a preset invalid status code. This holographic status word is injected into the smart contract stack. The smart contract uses a pre-defined bitwise AND instruction to perform a one-time bitwise AND operation between the holographic status word and the holographic rule mask carried in the transaction request. This mechanism ensures that all state data used for verification is locked into the same logical snapshot in the time dimension, so that no matter how many cross-domain departments the business rules involve, the on-chain compliance decision is always made within a single CPU instruction cycle. Completed within the specified time.

[0022] To prevent the risk of malicious tampering with rule parameters submitted by the client, this invention executes a rule integrity verification procedure based on dual-channel hash anchoring before the smart contract performs logical operations. This requires that the global hash digest of the currently effective rule set published by the rule-making body be pre-written into the persistent storage area of ​​the smart contract. The abstract describes how, using collision-resistant hash algorithms such as SHA-256, the standard rule configuration table is calculated. When the transaction initiator constructs a transaction verification request containing a set of rule feature codes, the same hash algorithm is used to calculate this set, generating a rule version anchor. And it is encapsulated in the request header. After the smart contract receives the request, it extracts... and in the storage area Perform byte-level comparison operations. When the comparison results are completely consistent, the contract loads the rule feature code set in the request into memory and starts the subsequent bit operation process; otherwise, it directly throws a parameter exception error and terminates the transaction. This procedure ensures that the rules executed by the smart contract strictly correspond to the valid version issued by the authoritative institution without increasing on-chain storage costs.

[0023] To address the non-binary compliance issues in financial and real estate transactions, this invention configures a conditional compensation verification logic based on residual mask extraction, and further subdivides the rule feature code set into rigid blocking masks. With flexible compensation mask When executing the main verification logic, the smart contract calculates the stake state vector. With the set of rule feature codes The XOR result, i.e. Through bitwise AND operation Extract the residual vector representing the difference between the current state and the target rule. The contract then proceeds to calculation. and The bitwise AND operation results in a non-zero value, indicating a non-exempt hard violation and generating a transaction blocking instruction. If the result is zero but... The fact that the value is not zero indicates that the difference falls within the compensable flexibility range. The contract initiates the risk hedging parameter calculation process: traversal The order of all values ​​of 1 ,by To find the corresponding unit risk compensation amount in the preset bit-to-amount mapping table. And according to the formula Calculate the total margin amount by summing them up. The final generation contains this Numerical conditional transaction permission instructions; to prevent the side-channel risk of user privacy leakage due to statistical analysis of holographic status words, this invention introduces a dynamic bitmap obfuscation mechanism based on transaction entropy, utilizing the inherent transaction hash value of each transaction. As a source of random entropy, both the oracle node and the transaction initiator execute a dynamic displacement parameter calculation procedure before generating a transaction request to calculate the displacement amount. Both parties used a circular left shift algorithm to adjust the equity state vector. With the set of rule feature codes Convert to confused states respectively and The smart contract performs bitwise logical operations directly on the two obfuscated bitmaps on the blockchain, based on the rotation invariance principle of bitwise operations under cyclic shifts, i.e. The zero / non-zero property of the computation result remains unchanged, the contract can make the correct compliance ruling, and the data stored on the chain... The data is presented as randomly distributed noise.

[0024] To eliminate the risk of erroneous system decisions due to abnormal off-chain data sources, this invention implements a three-valued logic adjudication procedure based on orthogonal confidence vectors, and extends the equity state vector into a set of mutually orthogonal vector pairs, namely, business value vectors carrying specific business states. Confidence vector of the validity of the data source When the oracle aggregates data, for each data source with a successful response and verified signature, it will... The corresponding flag position is set to 1, otherwise it is set to 0. The smart contract verification criterion is reconstructed into a dual logic gating: verification To confirm business compliance and verify The second layer of verification logic ensures that the data source behind all key bits involved in the rule determination is in a high-confidence state at the time of verification. If any key data is missing, resulting in a confidence level of 0, even if the business value is compliant, the circuit breaker mechanism will be triggered to block the transaction. To prevent malicious users from using the ambiguity of rule applicability for fraud, this invention constructs a rule deterministic addressing mechanism based on state invariants at the smart contract layer. It uses the objective attributes of the real estate itself as an index to lock the verification rules it follows. The protected type attribute bit field is defined in the holographic state word, storing the inherent attribute code of the real estate derived from the confirmation data. Before executing the verification, the smart contract extracts the value of the type attribute bit field through bitmasking operations, uses this value as the key, and directly addresses it in the pre-set attribute rule mapping table to extract the effective target rule feature code set. The contract uses the rule set derived by the system to replace the user rule parameters carried in the transaction request for subsequent logical operations.

[0025] Example 1: In a cross-regional commercial real estate transfer scenario, the seller is located in City A, the buyer is an investment institution in City B, and the subject matter is a commercial complex under construction in District C. This involves cross-regional heterogeneous compliance factors such as property status, land use, corporate credit, and tax payment. The City A real estate registration center node receives a transaction instruction containing the unique identifier of the real estate and the identifier of the commercial transfer business type. Based on a pre-set attribute rule mapping table, the system deterministically addresses and extracts the corresponding set of rule feature codes for the commercial real estate transfer. This set maps rules such as "not seized," "not mortgaged," "land transfer fee paid in full," and "buyer possesses commercial real estate investment qualifications" to specific binary bits in a 256-bit rule space, forming a rigid blocking mask. Define the bit fields corresponding to unseized and unmortgaged areas, and use flexible compensation masks. Define the bit field corresponding to the tax payment status, and the oracle node triggers a synchronization time window of 500ms. It also sends status query requests to the C District property registration database, the B City enterprise credit system, and the tax department interface.

[0026] The status codes returned by each data source are aggregated according to a preset rigid functional bit field structure. The physical status of the property is filled in the high bit field, the buyer's qualifications are filled in the middle bit field, and the tax status is filled in the low bit field, generating a holographic status word as the equity status vector. If the tax department's interface response delay exceeds The corresponding low-order segments are filled with preset invalid status codes. The smart contract executes a single-instruction decision on-chain and calculates the equity state vector. With the set of rule feature codes XOR result To extract the residual vector The calculation results show With rigid blocking mask The bitwise AND result is zero, confirming the compliance of the core property rights status. With flexible compensation mask A non-zero bitwise AND result indicates missing tax status data; the smart contract uses the residual vector. The preset position index and the mapping table between the position and the amount are based on the formula. Calculate the total amount of margin required to cover potential tax risks. The system generates a conditional transaction permission instruction containing the amount parameter, transforming the binary blocking determination of cross-domain compliance into risk pricing based on atomic state differences.

[0027] Example 2: This example aims to construct a verification environment that includes real network disturbances and non-ideal data source conditions. The core observation indicators of the experiment are the pass rate of transaction verification, the gas consumption of a single transaction, and the consistency of the system's adjudication logic under different rule mask configurations. The experimental platform is deployed on a private Ethereum test network consisting of 5 verification nodes. The smart contract is written and deployed in Solidity. To simulate a real real estate transaction ecosystem, three independent off-chain simulated data source services are constructed: property status service, tax status service, and credit status service. The property status service is configured as a high-availability node with a mean response time of 50ms. The credit status service introduces a random network latency that conforms to a normal distribution with a mean of 200ms and a standard deviation of 50ms. The tax status service is designed as a dependent variable, and its response behavior includes a preset service unavailability window to trigger the system's flexible compensation logic.

[0028] The experiment conducts stress tests on rigid blocking logic, setting rigid blocking masks in the set of rule feature codes. The corresponding bit field contains the seizure and mortgage status bits. 1000 transaction requests are continuously sent to the system, with 30% randomly mixed in as illegal transactions, which corresponds to the equity status vector returned by the property status service. In the experiment, the seizure or mortgage bit was set to 1, and a network disturbance with a packet loss rate of 5% was superimposed on the signal transmission link. The test results showed that all 300 illegal transactions were intercepted by the transaction blocking instructions generated by the smart contract, with a verification pass rate of 70%. The experiment focused on verifying the effectiveness of the flexible compensation mechanism, adjusting the rule configuration, and incorporating the tax payment status bit field into the flexible compensation mask. In 500 test transactions, the response to the tax status service was manually set to timeout, i.e., the confidence vector... The corresponding bit is 0, simulating a data source failure scenario. At this time, the equity state vector The default value for the tax status bit is 0, meaning no tax has been paid. The smart contract will detect this when... and A bitwise AND operation results in zero, but a bitwise AND operation results in zero. After the bitwise AND result is non-zero, the transaction is not blocked. Instead, the calculation of risk hedging parameters is automatically triggered. Table 1 shows the consistency verification results of the margin amount generated by the system and the preset mapping table under different residual vector inputs.

[0029] Table 1: Verification Table for Residual Vector and Margin Amount Calculation

[0030] Data shows that the system can accurately identify specific positions in the residual vector and perform linear accumulation calculations, outputting... The results perfectly match the theoretical values. Finally, a side-channel attack simulation was conducted to address the privacy protection mechanism. After enabling dynamic bitmap obfuscation based on transaction hashes, the input data of 100 consecutively stored transaction verification requests on-chain was extracted. Statistical analysis shows that although the business states behind these transactions are constant, such as without collateral, the obfuscated stake state vector stored on-chain... The bit distribution exhibits uniform randomness, and the Shannon entropy value is close to the theoretical maximum value of 8.0. For byte-level statistics, no statistical characteristics can be associated with specific business meanings.

[0031] Example 3: This example combines Figures 1 to 3 This document describes a method for verifying trusted transactions of real estate rights based on smart contract business rules. Figure 1 As shown, the verification process begins with receiving a transaction verification request and extracting the real estate identifier and rule feature code set. The logical path is divided into parallel data aggregation and rule verification stages. On one hand, the oracle node aggregates heterogeneous authoritative data sources in parallel and generates an equity state vector through holographic state word structure mapping. On the other hand, rule integrity verification is performed to compare the rule version anchor and global hash digest. Based on this, atomic logical decision is made by XORing the equity state vector and the rule feature code set. Then, the rigid blocking verification stage is entered, where the bitwise AND result of the residual vector and the rigid blocking mask is calculated. If the bitwise AND result is non-zero, a transaction blocking instruction is generated to block the illegal transaction. If the bitwise AND result is zero, it is further determined whether the residual vector is non-zero. In the case of a non-zero residual vector, a conditional permission instruction containing the calculation of risk hedging parameters, i.e., the total margin, is generated. In the case of a zero residual vector, a transaction pass instruction is generated to achieve full compliance release.

[0032] like Figure 2As shown, this chart constructs a performance observation coordinate system with test request numbers T1 to T20 as the horizontal axis and response latency in milliseconds as the vertical axis. It visually presents the latency fluctuations of the property status service, tax status service, and credit status service during continuous testing. The property status service is represented by a stable solid line with low latency, remaining in the low range around 50ms. The tax status service and credit status service are represented by dashed and dotted lines respectively, exhibiting oscillations in the high latency range of 180ms to 240ms. Figure 3 As shown, the process begins with the smart contract sending a status query request containing the real estate identifier. The oracle node then triggers a synchronization time window and sends query instructions for the property ownership status, tax payment status, and qualification status to heterogeneous data sources in parallel. After each data source returns the property ownership status code, tax status code, and qualification status code, the oracle node performs bit concatenation and aggregation according to the rigid functional bit field structure. If all data sources respond successfully, a complete holographic status word is returned to the smart contract. If any data source response times out, an invalid status code is filled in the corresponding bit field and a holographic status word with an invalid mark is returned, thereby completing the atomic synchronization of cross-domain states.

[0033] Example 4: In this example, to eliminate dynamic displacement parameters To address the uncertainty in the calculation process, the system executes a deterministic entropy extraction process based on transaction hashes, with the input data being the hash value of the current transaction request. The string is a 256-bit hexadecimal string. The first step in the process is to perform a byte-level slicing operation. Divided into 32 independent byte units The second step of the process uses the XOR folding algorithm, based on the formula... Calculate the 8-bit folding entropy value ,in This represents a bitwise XOR operation; the third step of the process introduces a method based on the current block height. The linear disturbance factor is used to calculate the final dynamic displacement parameters. This algorithm path ensures that even if two transactions have similar hash prefixes, the generated shift parameters will be identical. It can also produce discreteness due to differences in subsequent bytes and the time-varying nature of block height, thus effectively defending against predictive attacks targeting specific displacement amounts.

[0034] And for the confidence vector To address the issue of a lack of clear criteria for setting data source validity thresholds in the generation logic, this embodiment constructs an adaptive threshold calibration model based on historical response quality. The model defines the data source... Real-time response quality score The rating is determined by response time delay. Data signature verification result The decision is made jointly, and the specific calculation logic follows the formula. ,in The maximum tolerable latency allowed by the system is set to 5000ms. For Boolean validation, 1 represents a pass and 0 represents a fail. and For the preset weighting coefficients, and The model introduces a sliding time window. If the most recent 100 requests are included, calculate the average rating within that window. With variance Based on the assumption of normal distribution, the system dynamically sets the data source at the current time. Validity threshold ,when At that time, the confidence vector The corresponding bit is set to 1 only. This adaptive logic enables the system to automatically adapt to the network fluctuation characteristics of different data sources.

[0035] Determine the confidence level calculation model weight coefficients and At that time, a backtracking regression analysis procedure based on historical log data is executed to read the request logs of oracle nodes in a specific period in the past and extract the response latency of each data source. Signature verification result Given the input feature vector and the final blockchain confirmation status of the transaction as the truth label, a linear regression operation is performed on the input feature vector and the truth label using the least squares method to minimize the prediction mean square error. and The numerical calculation process is automatically triggered before the start of each verification cycle. The obtained coefficients are directly overwritten and written to the smart contract configuration storage area for subsequent generation of confidence vectors. Fixed calculation parameters enable adaptive updates based on measured data from the network environment; unit risk compensation amount in the quantized bit-to-amount mapping table. At that time, a dynamic mapping method based on the asset defect depreciation rate is adopted. This method involves periodically reading historical transaction records containing specific rights defects from the judicial auction database through a data interface to calculate the... The rule feature code corresponds to the average depreciation rate of the asset caused by the defect in rights. Multiplying the average depreciation rate by the current market value of the target asset assessed by a third party yields the corresponding rule feature code. Unit risk compensation amount The smart contract only reads data that has been calculated and stored in the oracle data table through the above steps. Value, based on the formula The cumulative calculation outputs the final risk hedging parameters.

[0036] Example 5: When the verification system of this invention is deployed in a new administrative jurisdiction, a standardized rule digitization and mapping configuration procedure needs to be executed to construct and populate the attribute rule mapping table in the smart contract. The system engineering team decomposes the current real estate transaction laws and regulations of the target jurisdiction into several indivisible atomic compliance conditions, and maps these conditions one by one to specific bit fields in the binary rule space according to the classification standard of rigid blocking and flexible compensation, generating a standardized set of rule feature codes. The system traverses all legally recognized real estate types and land nature classifications in the jurisdiction, assigns a unique attribute code as an index key to each type of asset with independent compliance requirements, and writes the corresponding set of rule feature codes as values ​​into the on-chain storage area.

[0037] Before the system accepts real-time transaction requests, it executes a full-link data source access and holographic state word mapping calibration procedure to ensure the accuracy of equity state vector generation. The oracle node defines the logical mapping relationship between structured data fields returned from heterogeneous external interfaces such as real estate registration, taxation and credit reporting and specific rigid functional bit fields in the holographic state word by configuring a parsing adapter. The system then starts an automated verification process, injecting simulated state data covering all business scenarios into each data source interface to monitor and verify whether each change in external state can accurately trigger the flipping of the corresponding binary bit in the holographic state word without generating crosstalk to other irrelevant bit fields.

[0038] Example 6: This example provides a standardized engineering implementation procedure for parameter calibration and functional testing of the verification system before deployment. The system is deployed on a test cluster consisting of 3 verification nodes and 1 monitoring node. The off-chain oracle service interface is connected to a data sandbox containing 1000 simulated real estate records. A holographic state word mapping calibration process is executed, randomly injecting a set of simulated real estate data containing specific legal status combinations, such as mortgaged but not seized, into the sandbox. This triggers the oracle to perform a state aggregation operation. The system automatically compares the generated holographic state word with the preset truth bitmap to verify the accuracy of the mapping logic. In 100 consecutive random tests, if any bit field mapping deviation occurs, the configuration parameters of the off-chain parser adapter are automatically adjusted according to the deviation type, such as bit offset or status code error, until the mapping results of all test cases are completely consistent with the truth.

[0039] The system also performs functional verification of residual mask extraction and risk pricing logic. Three typical rule configurations are pre-set in the system: pure rigid blocking rules, pure flexible compensation rules, and hybrid rules. For each rule set, simulated trading requests containing three types of violations—compliance, rigid violation, and flexible violation—are sent to the system. The system monitors the type of instructions output by the smart contract and the amount of risk hedging in real time. For flexible violation transactions under the hybrid rules, the total margin amount is calculated. The value is compared with the theoretical value calculated manually based on the bit amount mapping table and residual vector. If the error exceeds the preset precision threshold, such as 0.001ETH, the debugging process of the relevant arithmetic logic unit in the smart contract is triggered to correct potential rounding errors or overflow risks, and to ensure the accuracy and stability of the on-chain decision logic at the numerical calculation level.

[0040] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for verifying trusted transactions of real estate rights based on smart contract business rules, characterized in that, The method includes the following steps: Step 101: Receive transaction verification request, parse transaction verification request to extract real estate unique identifier and corresponding rule feature code set. The rule feature code set is divided into non-overlapping rigid blocking mask and flexible compensation mask in binary bit field. Step 102: Call the oracle interface based on the unique identifier of the real estate to obtain the rights status vector under the current time window. The rights status vector is a binary bitmap that maps the real estate's real-time legal status. Step 103: In the smart contract execution environment, perform atomic logic decision on the equity state vector. The atomic logic decision includes: calculating the result of the XOR logic operation between the equity state vector and the rule feature code set, and extracting the residual vector representing the difference bits between the current state and the target rule. Calculate the bitwise AND logical operation result of the residual vector and the rigid blocking mask; if the bitwise AND logical operation result is non-zero, generate a transaction blocking instruction; if the bitwise AND logical operation result is zero and the residual vector is non-zero, based on the bit order of the bits set in the residual vector, index the pre-set bit-to-amount mapping table in the smart contract to generate a conditional transaction permission instruction containing risk hedging parameters; if the bitwise AND logical operation result is zero and the residual vector is zero, generate a transaction pass instruction.

2. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, Step 102 includes: defining a holographic state word structure, which divides the binary data space into several non-overlapping rigid functional bit fields, which are used to map the property rights attribute status, the qualification attribute status of the transaction initiator, and the compliance attribute status of the transaction environment, respectively; receiving the holographic state word constructed by the oracle node as the equity state vector, which is generated by the oracle node in parallel aggregating feedback data from various heterogeneous authoritative data sources within the same time slice and filling it according to the rigid functional bit field structure; and constructing the rule feature code set into a holographic rule mask corresponding to the holographic state word structure to complete the joint verification of cross-domain business rules within a single instruction cycle.

3. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, The equity status vector includes a business value vector and a confidence vector that are independent of each other; before step 103, a data validity gating step is also included: the business value vector and the confidence vector are obtained respectively, and each bit in the confidence vector is used to characterize the validity of the data source of the corresponding bit in the business value vector at the time of generation; The steps include: calculating the bitwise AND result of the rule feature code set and the confidence vector; determining whether the bitwise AND result is completely consistent with the rule feature code set; and triggering the XOR logical operation result of the equity state vector and the rule feature code set only if the determination result is consistent.

4. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, Based on the bit order in the residual vector, the steps to generate a conditional trading permission instruction containing risk hedging parameters by indexing the pre-defined bit-to-amount mapping table in the smart contract include: extracting the position indices of all binary bits with true values ​​in the residual vector; traversing the position indices and obtaining the unit risk compensation amount corresponding to each position index from the bit-to-amount mapping table; and calculating the total margin amount in the risk hedging parameters according to the following formula. : ,in, For the residual vector, It is a positional index. This represents the total bit width of the residual vector. For bitwise AND operator, For the corresponding number in the bit-to-amount mapping table The unit risk compensation amount is calculated and the total margin amount is encapsulated in the conditional trading permission instruction.

5. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, The method also includes a dynamic obfuscation step for verification data based on transaction entropy: extracting the transaction hash value of the transaction verification request; calculating dynamic displacement parameters based on the transaction hash value; confirming that both the rule feature code set and the equity state vector have undergone homomorphic bit order permutation processing based on the dynamic displacement parameters before performing the step of calculating the XOR logical operation result of the equity state vector and the rule feature code set; and directly performing the logical operation of the rule feature code set and the equity state vector while maintaining the bit order permutation state.

6. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, The method also includes a rule integrity verification step: maintaining a global hash digest of the currently effective rule set published by the rule maker in the smart contract's storage area; extracting the rule version anchor point submitted along with the rule feature code set from the transaction verification request; performing a hash comparison operation to determine whether the rule version anchor point is consistent with the global hash digest; triggering step 103 only if consistent; if inconsistent, determining that the rule parameters of the transaction verification request are invalid and terminating the verification.

7. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, Step 101, which involves parsing the transaction verification request to extract the unique identifier of the real estate and the corresponding set of rule feature codes, is replaced by a rule-based deterministic addressing step based on state invariants. Specifically, this includes: pre-setting an attribute rule mapping table in the smart contract, which defines the correspondence between the inherent attribute codes of the real estate and the set of rule feature codes; performing a bitmask extraction operation on the equity state vector to parse out the type attribute bit field values ​​representing the inherent attributes of the real estate; using the type attribute bit field values ​​as an index to address and extract the corresponding target rule feature code set in the attribute rule mapping table; and using the target rule feature code set as a unique and valid logical mask for subsequent logical operations.

8. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 2, characterized in that, The holographic status word structure includes a high-order segment for mapping the physical attributes of real estate, a mid-order segment for mapping the attributes of the buyer, and a low-order segment for mapping the attributes of the transaction environment. The steps for an oracle node to perform off-chain atomic aggregation include: sending status query requests to multiple heterogeneous data sources; if any data source times out, filling the corresponding bit field of the holographic status word with a preset invalid status code; if all data sources respond successfully, concatenating the individual status codes according to the holographic status word structure to generate a unique holographic status word.

9. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, The steps for generating a transaction blocking instruction include: extracting the bit sequence of the non-zero bits in the result of a bitwise AND logical operation; retrieving the corresponding violation type description from a preset error code table based on the bit sequence; generating a transaction rejection receipt containing the violation type description; and writing the transaction rejection receipt to the transaction log area of ​​the blockchain for auditing.

10. The method for verifying trusted transactions of real estate rights based on smart contract business rules according to claim 1, characterized in that, The transaction verification request also includes a timestamp parameter; the method also includes: verifying whether the difference between the timestamp parameter and the current block timestamp is within a preset valid time window; only when the difference is within the valid time window, step 102 is executed; the entire process of atomic logic adjudication is completed within a single smart contract transaction and does not involve cross-block state storage operations.

Images