Domain name mistaken sealing prevention method and system based on block chain, electronic equipment and medium

Abstract

The invention provides a block chain-based domain name mistaken sealing prevention method and system, electronic equipment and a storage medium, and aims to solve the problems of insufficient timeliness, high mistaken sealing rate and easy tampering of page evidence storage. The method comprises the following steps: a mechanism to which a page belongs monitors newly adding and updating events of the page in real time; if it is monitored that the change exceeds a threshold value, generating a digital fingerprint through cooperative calculation of a timestamp and a current reputation score of a mechanism to which the page belongs by using a composite Hash algorithm; calling an intelligent contract interface, and registering the digital fingerprint, the timestamp and the reputation score to a block chain; the method comprises the following steps: acquiring a digital fingerprint of a page, so that a supervision end extracts a hash value of the current page according to the same hash algorithm when performing page detection, verifies the page according to the hash value and the digital fingerprint of the page to obtain a verification result, dynamically updates a reputation score of a mechanism to which the page belongs according to the verification result, and determines a page disposal strategy according to the reputation score. According to the invention, full-process automation can be realized, and the accuracy and the processing efficiency are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a domain name anti-mistaken blocking method based on blockchain, a domain name anti-mistaken blocking system based on blockchain, an electronic device, and a computer-readable storage medium. Background Art

[0002] Current internet domain name blocking relies primarily on traditional DNS (Domain Name System) blocking technology. Its core logic relies on manually reviewing and identifying offending pages, followed by blocking by the operator at the DNS level. However, this mechanism has significant flaws, including insufficient timeliness: the manual review process typically requires several hours to several days to respond, resulting in delayed handling of high-risk pages; a high false positive rate: static rule bases struggle to cope with dynamically changing web content. According to statistics, the false positive rate for financial H5 pages is as high as 15%-20%; and a lack of evidence: existing centralized evidence storage systems present the risk of data tampering, leading to disputes between regulators and financial institutions regarding the tracing of the basis for blocking.

[0003] In recent years, the industry has attempted to improve domain name governance through various technologies, but there are still obvious shortcomings. For example, AI-based content recognition: natural language processing (NLP) and image recognition technology are used to automatically detect illegal content, but the model's misjudgment rate is still higher than 10%, and it cannot solve the problem of evidence credibility; centralized evidence storage platform: some institutions establish electronic evidence storage systems to store page snapshots, but the single-point trust mechanism that relies on CA (Certificate Authority) certification is vulnerable to tampering by internal personnel; multi-party secure computing (MPC): attempts to verify compliance without exposing the original data, but the high computational complexity causes verification delays of more than minutes, making it difficult to meet real-time blocking requirements. Summary of the Invention

[0004] In order to at least solve the problems of insufficient timeliness, high false blocking rate and easy tampering of existing page evidence, the present disclosure provides a blockchain-based domain name false blocking prevention method, a blockchain-based domain name false blocking prevention system, an electronic device and a computer-readable storage medium. The method can prove the compliance of a page based on the tamper-proof evidence of the blockchain, realize the transparency of page compliance verification, and through reputation scoring, shift risk determination from static rule reliance to dynamic behavior analysis, significantly reducing the false blocking rate. Automated verification replaces manual review, realizing full process automation and significantly improving processing efficiency.

[0005] In a first aspect, the present disclosure provides a blockchain-based method for preventing mis-blocking of domain names, the method comprising:

[0006] The organization to which the page belongs monitors the page's new addition and update events in real time;

[0007] If the page content changes exceeding the threshold, a composite hash algorithm is used to generate a digital fingerprint for the page by collaboratively calculating the timestamp and the current reputation score of the organization to which the page belongs.

[0008] The smart contract interface is called to register the digital fingerprint, the corresponding timestamp and the reputation score of the organization to which the current page belongs to the blockchain; so that when the regulatory end performs page detection, the hash value of the current page is extracted according to the same composite hash algorithm, and the current page is verified according to the extracted hash value and the digital fingerprint of the page to obtain a verification result, and the reputation score of the organization to which the page belongs is dynamically updated according to the verification result, and the page disposal strategy is determined according to the reputation score to dispose of the page.

[0009] Furthermore, the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including:

[0010] Query the local cache at the edge node to see if the digital fingerprint of the current page is stored;

[0011] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0012] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0013] Furthermore, the use of a composite hash algorithm to generate a digital fingerprint for a page by collaboratively calculating a timestamp and a current reputation score of the organization to which the page belongs includes:

[0014] Generate a unique and irreversible digital fingerprint for the page through the core algorithm: H = SHA3-256 (C||T||[P*100]||Nonce);

[0015] Among them, C is the complete content of the H5 page, T is the current timestamp, P is the current reputation score of the organization to which the page belongs, and Nonce is a random number.

[0016] Furthermore, the method further comprises:

[0017] In the process of generating digital fingerprints, sensitive data processing is completed in the TEE (Trusted execution environment), the original page content is isolated, and the memory data is fully encrypted based on Intel SGX (Software Guard Extensions) technology.

[0018] In a second aspect, the present disclosure provides a blockchain-based method for preventing mis-blocking of domain names, the method comprising:

[0019] When the supervisory end performs page detection, it extracts the hash value of the current page through a composite hash algorithm;

[0020] The current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is monitored by the page's organization in real time for new and updated events. When the page content changes exceeding a threshold, the same composite hash algorithm is used to generate a page through collaborative calculation of the timestamp and the current reputation score of the page's organization. The page's organization calls the smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the current page's organization on the blockchain;

[0021] Dynamically update the reputation score of the organization to which the page belongs based on the verification results;

[0022] Determine the page handling strategy based on the reputation score and handle the page.

[0023] Furthermore, the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including:

[0024] Query the local cache at the edge node to see if the digital fingerprint of the current page is stored;

[0025] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0026] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0027] Furthermore, dynamically updating the reputation score of the organization to which the page belongs based on the verification result includes:

[0028] The reputation score is dynamically updated based on the verification results using the following formula:

[0029]

[0030] Among them, P prior is the current reputation score, P new This is the updated reputation score.

[0031] Furthermore, the method further comprises:

[0032] In the edge computing node, the digital fingerprint of the cached frequently accessed and high-reputation pages is selected using the following formula;

[0033] CachePriority = α * access frequency + β * P

[0034] Where CachePriority is the cache score of the page. The higher the score, the greater the cache probability. α and β are adjustable weights, and P is the reputation score; and,

[0035] Use the LRU (Least Recently Used) cache eviction strategy algorithm to store the active digital fingerprints within a preset time.

[0036] Furthermore, the determining the page handling strategy according to the reputation score includes:

[0037] If the reputation score ≥ 0.9, then automatically release;

[0038] If the reputation score satisfies: Q ≤ reputation score < 0.9, then conduct a manual review of the page;

[0039] If the reputation score < Q, then immediately ban;

[0040] Where Q is the determination threshold, and it is dynamically adjusted according to the global risk situation.

[0041] Furthermore, the method further includes:

[0042] Dynamically adjust the determination threshold according to the global risk situation. The calculation formula is:

[0043]

[0044] Where θ(t) is the dynamically adjusted determination threshold, range: 0.0 - 1.0, θ base is the basic determination threshold, k is the adjustment coefficient, ∑RiskEvent 24h is the total number of risk events in the past 24 hours, and Ntotal is the total number of verification events in the past 24 hours.

[0045] Furthermore, the invoking the zero - knowledge proof verification function to verify the current page includes:

[0046] Invoke the following zero - knowledge proof verification function to conduct compliance verification on the page:

[0047] π = Prove(CRS, (H, Sig), ComplianceRules)

[0048] Verify(CRS, π) → {0, 1}

[0049] Among them, π is zero-knowledge proof, CRS is the public reference string, H is the page digital fingerprint, Sig is the institutional signature, and ComplianceRules is the compliance rules. The rule sets of different time periods are dynamically loaded through smart contracts to achieve the temporal and spatial adaptability of compliance verification.

[0050] In a third aspect, the present disclosure provides a blockchain-based domain name anti-misblocking system, the system including a page-affiliating organization, the page-affiliating organization including:

[0051] The monitoring module is set to monitor the new and updated events of the page in real time;

[0052] a generation module configured to generate a digital fingerprint for a page using a composite hash algorithm by collaboratively calculating a timestamp and a current reputation score of the organization to which the page belongs, if the monitoring module monitors that a change in the page content exceeds a threshold;

[0053] The on-chain module is configured to call the smart contract interface to register the digital fingerprint, the corresponding timestamp and the reputation score of the institution to which the current page belongs to the blockchain; so that when the regulatory end performs page detection, the hash value of the current page is extracted according to the same composite hash algorithm, and the current page is verified according to the extracted hash value and the digital fingerprint of the page to obtain a verification result, and the reputation score of the institution to which the page belongs is dynamically updated according to the verification result, and the page disposal strategy is determined according to the reputation score to dispose of the page.

[0054] In a fourth aspect, the present disclosure provides a blockchain-based domain name anti-mistaken blocking system, the system including a supervisory end, the supervisory end including:

[0055] An extraction module is configured to extract a hash value of a current page through a composite hash algorithm when performing page detection;

[0056] A verification module is configured to verify the current page based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is generated by the organization to which the page belongs by monitoring the addition and update events of the page in real time. When the page content changes exceeding a threshold, the same composite hash algorithm is used to collaboratively calculate the timestamp and the current reputation score of the organization to which the page belongs. The organization to which the page belongs calls a smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the organization to which the current page belongs on the blockchain;

[0057] A rating update module, which is configured to dynamically update the reputation score of the organization to which the page belongs based on the verification results;

[0058] The disposal module is configured to determine a page disposal strategy based on the reputation score and to dispose of the page.

[0059] In a fifth aspect, the present disclosure provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the blockchain-based domain name anti-misblocking method as described in any one of the first and second aspects.

[0060] In a sixth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the blockchain-based domain name anti-misblocking method described in any one of the first and second aspects above is implemented.

[0061] Beneficial effects:

[0062] The present disclosure provides a blockchain-based domain name anti-misblocking method, a blockchain-based domain name anti-misblocking system, an electronic device, and a storage medium. These methods can prove the compliance of a webpage based on the tamper-proof evidence of the blockchain, thereby achieving transparency in the verification of webpage compliance. Through cross-chain oracles, the data silos of financial institutions, regulatory authorities, and operators are connected to achieve intelligence sharing. Through reputation scoring, risk assessment is shifted from static rule reliance to dynamic behavior analysis, significantly reducing the misblocking rate. Automated verification replaces manual review, achieving full-process automation and significantly improving processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A flowchart of a method for preventing mis-blocking of domain names based on blockchain provided in the first embodiment of the present disclosure;

[0064] Figure 2 A flowchart of a method for preventing mis-blocking of domain names based on blockchain provided in the second embodiment of the present disclosure;

[0065] Figure 3 A core architecture diagram of a blockchain-based domain name anti-mistaken blocking system provided in an embodiment of the present disclosure;

[0066] Figure 4 This is an architectural diagram of an organization to which a page belongs, provided in the fourth embodiment of the present disclosure;

[0067] Figure 5 This is an architecture diagram of a supervisory terminal provided in the fifth embodiment of the present disclosure;

[0068] Figure 6 This is an architectural diagram of an electronic device provided in Example 6 of the present disclosure. DETAILED DESCRIPTION

[0069] To enable those skilled in the art to better understand the technical solutions of the present disclosure, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments and drawings described herein are only used to explain the present disclosure, rather than to limit the present disclosure.

[0070] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence; and, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be arbitrarily combined with each other.

[0071] The terms used in the embodiments of the present disclosure are for the purpose of describing specific embodiments only and are not intended to limit the present disclosure. The singular forms "a," "an," "the," and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0072] In the subsequent description, suffixes such as "module," "component," or "unit" used to represent elements are used only to facilitate the description of the present disclosure and have no specific meaning. Therefore, "module," "component," or "unit" may be used interchangeably.

[0073] The following is a detailed description of the technical solutions of the present invention and how the technical solutions of the present invention solve the technical problems in the prior art with specific embodiments. It will be appreciated that, in the embodiments of the present application, the execution subject may perform some or all of the steps in the embodiments of the present application, and these steps or operations are merely examples. The embodiments of the present application may also perform other operations or variations of various operations. In addition, the various steps may be performed in different orders as presented in the embodiments of the present application, and it may not be necessary to perform all the operations in the embodiments of the present application. Furthermore, the following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in certain embodiments.

[0074] Figure 1 A flowchart of a method for preventing mis-blocking of a domain name based on blockchain is provided in the first embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0075] Step S101: The organization to which the page belongs monitors the new addition and update events of the page in real time;

[0076] Step S102: If the page content change is detected to exceed a threshold, a composite hash algorithm is used to generate a digital fingerprint for the page by collaboratively calculating the timestamp and the current reputation score of the organization to which the page belongs;

[0077] Step S103: Call the smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the organization to which the current page belongs to the blockchain; so that when the regulatory end performs page detection, the hash value of the current page is extracted according to the same composite hash algorithm, and the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, and the reputation score of the organization to which the page belongs is dynamically updated according to the verification result, and the page disposal strategy is determined according to the reputation score to dispose of the page.

[0078] The disclosed embodiment uses a dynamic digital identity authentication system based on blockchain to address the problem of incorrectly blocked pages of various institutions. By generating unique digital fingerprints, on-chain smart contract registration, digital fingerprint verification and other technologies, page evidence storage and supervision coordination are achieved.

[0079] Taking the H5 page of a financial institution as an example, the implementation process includes: using the H5 page collector to monitor the new and updated events of the financial institution's H5 page in real time, triggering the digital fingerprint generation process; the monitoring process is based on the event-driven architecture of the webhook (network hook), supporting content change threshold detection (the default trigger is 5% content change). If the process is triggered, the fingerprint generation engine calculates the page hash;

[0080] By combining the timestamp with the reputation score, a composite hash algorithm is used to generate a unique and irreversible digital fingerprint, such as a 256-bit hash value, which includes anti-tampering and anti-replay attack mechanisms. The reputation score is quantized into an integer for hashing, allowing the fingerprint to simultaneously reflect both the content and the credit status. The fingerprint reflects the content, time, and reputation status simultaneously, preventing reusing old fingerprints on reputation-degraded pages. An attacker would need to simultaneously decrypt the content and reputation status to forge the fingerprint, ensuring that the stored data is irreversible and unforgeable, effectively defending against page content tampering and replay attacks.

[0081] The institution then calls the smart contract interface, which encapsulates blockchain interaction protocols, enabling digital identity registration, document upload, and credit score queries. The smart contract interface supports multi-chain adaptation (Fabric / Ethereum), with transaction confirmation delays of ≤3 seconds. After the institution registers the page's digital fingerprint, the corresponding timestamp, and the credit score of the institution to which the page belongs on the blockchain, the blockchain network layer manages the on-chain registration, query, and status updates of the digital fingerprint. The data structure is as follows:

[0082] structIdentity{

[0083] bytes32 hash; / / digital fingerprint

[0084] uint256 timestamp; / / certificate storage time

[0085] addressissuer; / / Institution address

[0086] float reputation; / / Reputation score (0.0-1.0, excluding 1.0)

[0087] }

[0088] When the regulatory agency detects that the page has been accessed multiple times, detects suspicious page access requests, or requires page inspection, it extracts the hash value of the current page using the same composite hash algorithm. The page is verified based on the extracted hash value and the digital fingerprint of the page, and the currently calculated hash value is compared with the original data fingerprint stored on the chain. If the verification is consistent, the page content has not been tampered with and the verification passes. If it is inconsistent, the page content has been modified and the verification fails. The verification result is obtained. Through the parameter consistency of the composite hash algorithm, the strong anti-collision property of the hash function, and the tamper-proof storage of the blockchain, the regulatory agency can efficiently and accurately detect page tampering.

[0089] After obtaining the verification results, the regulatory agency will dynamically update the reputation score of the institution to which the page belongs based on the verification results, and determine the page disposal strategy based on the reputation score to dispose of the page.

[0090] Digital fingerprints enable instant compliance checks, while the reputation scoring mechanism is designed to dynamically adjust trust levels and optimize long-term risk management. Pages with high reputation scores can be automatically released even if they occasionally experience verification delays or minor errors, reducing manual intervention. Pages with low reputation scores may still require manual review even if they pass a single verification to prevent the spread of potential risks. For example, if a financial institution with long-standing compliance (high score) fails to update its fingerprint in a timely manner due to temporary network issues, the system may still automatically release it. If a high-risk institution submits a compliant page for the first time (low score), even if it passes verification, it still requires manual review. Determining page handling strategies based on reputation scores can address dynamic trust issues (long-term behavioral assessment and risk adaptation), over-quantify long-term credit status, and compensate for the limitations of single verification. It can also dynamically optimize resource allocation and risk strategies, improve system efficiency and security, and enhance defenses against complex attacks (such as persistent tampering and credit fraud). Relying solely on local caching and on-chain verification would lack the ability to dynamically adapt to historical behavior and global risks, potentially leading to either false blocking (overly strict) or missed blocking (overly lenient). Therefore, the disclosed embodiments achieve precise risk control by introducing reputation scoring.

[0091] After obtaining the credit score, the regulatory agency determines the page handling strategy based on the credit score and handles the page, such as releasing it, immediately banning it, or further reviewing it. Different handling methods are taken according to the level of the credit score, and instructions are issued through the emergency response interface (supporting Syslog / SNMP (Simple Network Management Protocol)); and when banning a page, the financial institution is notified and marked as high-risk.

[0092] Regulators can also use behavioral analyzers to compile statistics on recent verification logs and identify unusual patterns (such as multiple verifications within a short period of time or frequent page updates). Using time series analysis (ARIMA models) and correlation graph mining, regulators' off-chain threat intelligence (such as the latest ban rules) is securely synchronized to the blockchain via a cross-chain oracle. This synchronization data security mechanism utilizes TLS 1.3 encrypted transmission and multi-signature verification to ensure data security. The compliance rule base within the smart contract (such as specific text permissible promotional periods) is updated on the blockchain.

[0093] The disclosed embodiments can prove the compliance of a page based on the tamper-proof evidence of the blockchain, thereby achieving transparency in page compliance verification; through cross-chain oracles, the data silos of financial institutions, regulatory authorities, and operators are connected to achieve intelligence sharing; through reputation scoring, risk assessment is shifted from static rule reliance to dynamic behavior analysis, significantly reducing the false blocking rate; and automated verification replaces manual review to achieve full process automation, significantly improving processing efficiency.

[0094] Furthermore, the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including:

[0095] Query the local cache at the edge node to see if the digital fingerprint of the current page is stored;

[0096] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0097] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0098] When the regulatory agency verifies a page, it first verifies it through the edge node: the edge node queries the local cache to see if the digital fingerprint of the page is stored. If it misses, it initiates on-chain zero-knowledge proof verification. The edge node obtains the digital fingerprint of frequently accessed and high-reputation pages from the blockchain network for caching. It is deployed in a provincial regulatory data center, close to the source of user access, to achieve low-latency processing. The local hash comparison delay is ≤50ms, which can quickly respond to most requests and avoid users waiting too long due to on-chain verification. It can achieve fast page verification, improve response speed and user experience. For low-frequency or high-risk requests that miss the cache, on-chain verification is performed through zero-knowledge proof (zk-SNARKs), with a delay of ≤150ms. The overall system still maintains a response capability of seconds. Through a dual-channel verification strategy: local cache priority + on-chain zero-knowledge proof verification, it can improve response speed, optimize resource allocation, reduce costs, and reduce on-chain load.

[0099] Digital fingerprint comparisons can be used to identify content changes: hash functions are highly collision-resistant, meaning even minor changes to the page content will result in significantly different hash values. Parameter solidification: The timestamp (T) and random number (Nonce) are permanently stored on the blockchain, preventing attackers from tampering with or reusing old parameters to generate a valid hash. Zero-knowledge proof verification verifies page compliance without revealing specific content by storing compliance verification circuits (such as rules for the absence of sensitive words and legal registration numbers) and the generated proof documents. The technical standard utilizes the Groth16 protocol, with a single proof generation time of ≤2 seconds.

[0100] Furthermore, the use of a composite hash algorithm to generate a digital fingerprint for a page by collaboratively calculating a timestamp and a current reputation score of the organization to which the page belongs includes:

[0101] Generate a unique and irreversible digital fingerprint for the page through the core algorithm: H = SHA3-256 (C||T||[P*100]||Nonce);

[0102] Among them, C is the complete content of the H5 page, T is the current timestamp, P is the current reputation score of the organization to which the page belongs, and Nonce is a random number.

[0103] The fingerprint generation engine of the embodiment of the present disclosure generates not a simple hash but a unique and irreversible digital fingerprint through the collaborative calculation of timestamp and reputation score, which includes anti-tampering and anti-replay attack mechanisms.

[0104] Core algorithm: H = SHA3-256(C||T||[P*100]||Nonce);

[0105] Where C is the complete content of the H5 page (HTML, CSS, and JS), T is the current timestamp (accurate to milliseconds), P is the current reputation score, and Nonce is a random number (to prevent replay attacks). The hash value generated by the SHA3-256 algorithm is 256 bits (32 bytes) and is usually expressed as a hexadecimal string.

[0106] Reputation scores are quantified into integers and hashed, allowing fingerprints to simultaneously reflect both content and credit status. Fingerprints reflect content, time, and reputation status, preventing reusing old fingerprints on pages with downgraded reputations. An attacker must simultaneously crack both content and reputation status to forge a fingerprint. Output: 256-bit hash value, capable of processing ≥ 1000 pages per second.

[0107] Furthermore, the method further comprises:

[0108] In the process of generating digital fingerprints, sensitive data processing is completed in the trusted execution environment TEE, the original page content is isolated, and based on Intel SGX technology, the memory data is fully encrypted.

[0109] TEE provides hardware-level system isolation and root of trust, supports data security capabilities based on technical trust, and ensures that the code and data loaded within the secure area are protected in terms of confidentiality and integrity; Intel SGX technology creates a secure and isolated Enclave to ensure that sensitive data involved in the digital fingerprint generation process (such as page original content, timestamps, and random numbers) is only processed in encrypted memory. Even if the host operating system or hardware is attacked, the memory data cannot be directly read or tampered with. When data is calculated in the Enclave, the memory is fully encrypted (such as AES-GCM) to prevent physical attacks (such as cold start attacks) or side-channel attacks from stealing sensitive information.

[0110] The digital fingerprint generated by the TEE is written directly to the blockchain via a smart contract, ensuring the transparent and tamper-proof storage process. The encryption capabilities of SGX complement the distributed ledger nature of the blockchain to build an end-to-end trusted evidence chain.

[0111] Data Privacy and Security: Sensitive information is fully encrypted and isolated to protect against external and internal threats. Tamper and Attack Resistance: Ensures fingerprint authenticity and prevents complex threats like replay and supply chain attacks. Efficiency and Compliance: Hardware acceleration supports high-performance computing while meeting privacy regulations. Technical Synergy: Seamless integration with blockchain and zero-knowledge proofs creates an end-to-end trusted evidence storage system.

[0112] The disclosed embodiments ensure the compliance and reliability of verification through digital fingerprints, the blockchain's tamper-proof evidence storage capabilities, and a dual-channel verification strategy of edge computing nodes and zero-knowledge proofs (zk-SNARKs); a dynamic reputation scoring mechanism combined with on-chain behavioral data adjusts the score in real time, shifting risk assessment from static rule reliance to dynamic behavior analysis, significantly reducing the false blocking rate; and through the local cache and on-chain verification dual channels of the edge computing architecture, a verification response within seconds can be achieved, solving the high latency problem of traditional manual review; the burden on regulators is reduced through the automated interaction between smart contracts and zero-knowledge proof libraries, as well as automated verification and hierarchical disposal strategies, while distributed governance is achieved through the edge computing architecture, reducing the need for manual intervention, and the verification process can achieve efficiency improvements and resource optimization; and by building a multi-party alliance chain network (financial institutions + regulators), data silos can be broken and real-time synchronization of threat intelligence and rules can be achieved.

[0113] like Figure 2 As shown, the second embodiment of the present disclosure further provides a method for preventing misblocking of domain names based on blockchain, the method comprising:

[0114] Step S201: When performing page detection, the supervisory end extracts the hash value of the current page using a composite hash algorithm;

[0115] Step S202: The current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is generated by the page's organization by monitoring the addition and update events of the page in real time. When the page content changes exceeding a threshold, the same composite hash algorithm is used to collaboratively calculate the timestamp and the current reputation score of the page's organization. The page's organization then calls the smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the current page's organization on the blockchain.

[0116] Step S203: Dynamically update the reputation score of the organization to which the page belongs based on the verification result;

[0117] Step S204: Determine a page handling strategy based on the reputation score and handle the page.

[0118] The disclosed embodiment implements a blockchain-based domain name anti-misblocking method from the regulatory side. When the regulatory side detects that the page has been visited multiple times or detects a suspicious page access request, it will initiate a detection of the page, extract the current page hash, and compare and verify it with the digital fingerprint of the page registered in the blockchain to obtain a verification result, and update the reputation score of the organization to which the page belongs based on the verification result, thereby determining the disposal measures for the page. The implementation process corresponds to the process of Example 1 and will not be repeated here.

[0119] Furthermore, the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including:

[0120] Query the local cache at the edge node to see if the digital fingerprint of the current page is stored;

[0121] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0122] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0123] When performing page verification, local verification is performed first, and the cached digital fingerprint library is queried first at the edge node. If a hit is found, the verification result is returned directly; if a hit is found, an on-chain zero-knowledge proof verification is initiated; compliance is verified through the zero-knowledge proof library, and the credit scoring contract updates the score, thereby issuing a ban / release instruction based on the score.

[0124] Furthermore, dynamically updating the reputation score of the organization to which the page belongs based on the verification result includes:

[0125] The reputation score is dynamically updated based on the verification results using the following formula:

[0126]

[0127] Among them, P prior is the current reputation score, P new This is the updated reputation score.

[0128] When verification results are received, using the formula above can achieve a slight score increase, with the increase decreasing as it approaches 1.0. When verification fails, using the formula below can achieve a significant score decrease, with the decrease decreasing as it approaches 0.0. Based on historical reputation scores and verification results, an updated reputation score is generated. A dynamic downgrade mechanism allows for rapid isolation of high-risk pages to prevent the spread of risk. Furthermore, organizations with very low scores can be investigated and required to make corrections.

[0129] Furthermore, the method further comprises:

[0130] In the edge computing node, the digital fingerprint of the cached frequently accessed and high-reputation pages is selected using the following formula;

[0131] CachePriority = α * access frequency + β * P

[0132] Where CachePriority is the cache score of the page. The higher the score, the greater the cache probability. α and β are adjustable weights, and P is the reputation score; and,

[0133] Use the LRU cache eviction strategy algorithm to store the active digital fingerprints within a preset time.

[0134] Pages with high-frequency access need to respond quickly to reduce the user request latency. Pages with high reputation are usually safer and compliant. After caching, it can reduce the risk verification overhead. By calculating the cache score of the page through the formula, pages that are both popular and trustworthy can be preferentially cached, avoiding wasting resources on low-value or high-risk content; by flexibly adjusting the weights α and β, different scenario requirements can be adapted. For example: In high-traffic scenarios: increase α to preferentially cache high-frequency pages to improve the response speed. In high-risk scenarios: increase β to preferentially cache high-reputation pages to enhance security.

[0135] The preset time can be set to 7 days. Combine the LRU (Least Recently Used) eviction strategy with a time window to preferentially evict pages that have not been accessed for a long time and retain recent active data. Combining the time window ensures the timeliness of the cached data. For example, after a promotion event ends, the relevant pages are gradually evicted to free up space for new active content. It can also prevent the cache from being occupied by invalid data due to sudden traffic (such as a short-term attack). Through the above methods, the cache hit rate of the edge computing node can be improved. High-frequency and high-reputation pages will stay in the cache for a long time, and the hit rate ≥ 95%, reducing the amount of on-chain verification requests. And the response latency of the edge node can be controlled within ≤ 50ms, significantly optimizing the user experience.

[0136] Further, the determining the page handling strategy according to the reputation score includes:

[0137] If the reputation score ≥ 0.9, it is automatically released;

[0138] If the reputation score satisfies: Q ≤ reputation score < 0.9, the page is manually reviewed;

[0139] If the reputation score < Q, it is immediately blocked;

[0140] Where Q is the determination threshold and is dynamically adjusted according to the global risk situation.

[0141] Automatically determine the page disposal strategy according to the reputation score. If the reputation score ≥ 0.9, it indicates that the institution has had no behavior of page verification failure for a long time or very few such behaviors, then the page directly passes the verification without manual intervention, which is applicable to high-reputation institutions with long-term compliance (such as state-owned banks), reducing the operational friction of compliant institutions and improving service efficiency. When Q ≤ reputation score < 0.9, it triggers a secondary review by the supervisor, comprehensively judging in combination with the page content and historical behavior to prevent missealing caused by accidental errors (such as temporary copy adjustment). When the reputation score < Q, the page is automatically blocked and the institution is notified, which is applicable to high-risk or frequently违规 pages (such as frequent tampering or involving illegal content), strictly controlling low-reputation pages: through a dynamic score reduction mechanism, quickly isolating high-risk pages to prevent the spread of risks. High-reputation pages are automatically released, and only a small number of medium- and low-risk pages require manual review, saving the supervision labor cost.

[0142] The determination threshold is automatically adjusted according to risk events. When the system detects a large-scale attack (such as multiple page tampering within a short period), the threshold is automatically lowered to enhance the strictness of blocking. For example, if the risk events increase by 50% in the past 24 hours, the threshold drops from 0.6 to 0.55 to expand the blocking scope to cope with the threat.

[0143] Furthermore, the method further includes:

[0144] Dynamically adjust the determination threshold according to the global risk situation, and the calculation formula is:

[0145]

[0146] where θ(t) is the dynamically adjusted determination threshold, with the range: 0.0 - 1.0 (excluding the endpoints), θ base is the basic determination threshold, k is the adjustment coefficient, ∑RiskEvent 24h is the total number of risk events within the past 24 hours, and Ntotal is the total number of verification events within the past 24 hours.

[0147] θ base is the initial threshold of the system, representing the default determination standard in the absence of risk events, with a default value of 0.6. The logarithmic term: is used to smooth the impact of risk events and avoid drastic fluctuations in the threshold. The adjustment coefficient k controls the sensitivity of the threshold to risk events, with a default value of 0.05.

[0148] By dynamically adjusting the determination threshold, sudden risks can be coped with; for example, during a certain shopping festival, attackers concentrated on tampering with promotion pages. After the system detected a sharp increase in risk events, the threshold was dynamically adjusted from 0.6 to 0.55, blocking suspicious pages in advance to contain the impact of the attack.

[0149] Through a reputation-based, tiered approach, regulators achieve a balance between efficiency and security: automating the majority of compliance requests, concentrating resources on high-risk incidents; dynamic risk response: scores and thresholds adjust in real time based on behavioral data, enhancing system flexibility and attack resilience; and transparent compliance governance: blockchain-based evidence storage and zero-knowledge proofs ensure an auditable and privacy-friendly process. This not only addresses the delays and misjudgments inherent in traditional manual review, but also provides a scalable and adaptive solution for regulation in the digital age.

[0150] Furthermore, calling the zero-knowledge proof verification function to verify the current page includes:

[0151] Call the following zero-knowledge proof verification function to verify the compliance of the page:

[0152] π=Prove(CRS,(H,Sig),ComplianceRules)

[0153] Verify(CRS,π)→{0,1}

[0154] Among them, π is zero-knowledge proof, CRS is the public reference string, H is the page digital fingerprint, Sig is the institutional signature, and ComplianceRules is the compliance rules. The rule sets of different time periods are dynamically loaded through smart contracts to achieve the temporal and spatial adaptability of compliance verification.

[0155] The digital fingerprint H of the page is generated by the SHA3-256 algorithm. It can verify whether the page has been changed, and the digital signature Sig of the financial institution can be used for identity authentication. The prover uses CRS, page fingerprint, signature and compliance rules to generate a zero-knowledge proof π. This proof can verify that the content of the page complies with the rules without revealing the specific content of the page. The output result of the verification function Verify is 0 (failure) or 1 (pass). Prove() and Verify() are two core functions, executed by the prover (Prover) and the verifier (Verifier) respectively. Prove() function: The prover uses secret information and public parameters to generate a mathematical proof (proof) to prove to the verifier that a statement is true without revealing the secret itself. Verify() is used by the verifier to check the validity of the proof and confirm whether the statement is true without having to access the secret information.

[0156] Zero-knowledge proof verification uses a compliance verification circuit to store predefined rule logic (such as a list of sensitive words and the format of a registration number) and embed a time-sensitive strategy: ComplianceRules = BaseRules∧(TimeWindow→SpecialRules). Smart contracts dynamically load rule sets for different time periods to achieve spatiotemporal adaptability of compliance verification. BaseRules: Basic rules (such as prohibiting illegal content), TimeWindow→SpecialRules: Special rules allowed within the time window (such as specific copywriting during promotional periods). Smart contracts automatically switch rule sets based on timestamps. For example: During non-promotional periods: Only BaseRules (strict mode) applies. During promotional periods: SpecialRules is enabled (allowing specific marketing copywriting). Privacy-preserving compliance verification is achieved through the Prove and Verify formulas, ensuring that regulators can determine legality without viewing the page content. Time- and spatiotemporal-sensitive rule switching is achieved through smart contracts, balancing regulatory strictness and business flexibility. The zero-knowledge proof verification technology standard adopts the Groth16 protocol, and the single proof generation time is ≤2 seconds; the Groth16 protocol and CRS mechanism ensure the rapid generation and verification of proofs while resisting the risk of data leakage.

[0157] Regulators can also use behavioral analyzers to compile statistics on recent verification logs and identify unusual patterns (such as multiple verifications within a short period of time or frequent page updates). Using time series analysis (ARIMA models) and correlation graph mining, regulators' off-chain threat intelligence (such as the latest ban rules) is securely synchronized to the blockchain via a cross-chain oracle. This synchronization data security mechanism utilizes TLS 1.3 encrypted transmission and multi-signature verification to ensure data security. The compliance rule base within the smart contract (such as specific text permissible promotional periods) is updated on the blockchain.

[0158] After determining the disposal measures, the emergency response interface is connected to the supervision and ban system to realize the automatic issuance of graded disposal instructions; the interface protocol supports the Syslog / SNMP standard protocol, and the instruction delay is ≤200ms.

[0159] The disclosed embodiments ensure the compliance and reliability of verification through digital fingerprints, the blockchain's tamper-proof evidence storage capabilities, and a dual-channel verification strategy of edge computing nodes and zero-knowledge proofs (zk-SNARKs); a dynamic reputation scoring mechanism combined with on-chain behavioral data adjusts the score in real time, shifting risk assessment from static rule reliance to dynamic behavior analysis, significantly reducing the false blocking rate; and through the local cache and on-chain verification dual channels of the edge computing architecture, a verification response within seconds can be achieved, solving the high latency problem of traditional manual review; the burden on regulators is reduced through the automated interaction between smart contracts and zero-knowledge proof libraries, as well as automated verification and hierarchical disposal strategies, while distributed governance is achieved through the edge computing architecture, reducing the need for manual intervention, and the verification process can achieve efficiency improvements and resource optimization; and by building a multi-party alliance chain network (financial institutions + regulators), data silos can be broken and real-time synchronization of threat intelligence and rules can be achieved.

[0160] The third embodiment of the present disclosure also provides a domain name anti-misblocking method based on blockchain, the core architecture is as follows: Figure 3 As shown, from bottom to top:

[0161] The financial institution's evidence storage layer, through the H5 page collector, monitors the new and updated events of the financial institution's H5 page in real time, triggering the digital fingerprint generation process. The fingerprint generation engine generates a unique and irreversible digital fingerprint through the collaborative calculation of timestamp and credit score; completes sensitive data processing in the trusted execution environment (TEE) through the privacy protection agent, and isolates the original page content; and the blockchain interaction protocol is encapsulated by the smart contract interface to realize digital identity registration, proof document upload, and credit score query.

[0162] The blockchain network layer implements the identity registration contract and manages the on-chain registration, query and status update of digital fingerprints; the zero-knowledge proof library stores compliance verification circuits (such as rules such as no sensitive words and legal registration numbers) and generated certification documents; the reputation scoring contract dynamically updates the reputation score based on the verification results; the cross-chain oracle securely synchronizes the off-chain threat intelligence of the regulatory authorities (such as the latest ban rules) to the blockchain.

[0163] The regulatory verification layer integrates access frequency and reputation through a comprehensive caching strategy in edge computing nodes, deploys lightweight verification nodes in provincial regulatory data centers, and caches the digital fingerprints of pages with high frequency access and high reputation values; the real-time verification engine performs dual-channel verification (local cache comparison + on-chain zero-knowledge proof verification); the risk decision module dynamically adjusts the disposal strategy and threshold rules based on the reputation score; and connects to the regulatory ban system through the emergency response interface to realize the automatic issuance of graded disposal instructions.

[0164] The dynamic reputation management layer analyzes on-chain verification logs through a behavior analyzer to extract risk characteristics (such as high-frequency modifications and cross-institutional correlation risks); the threshold adaptive module dynamically adjusts the judgment threshold based on the global risk situation.

[0165] The supervision verification layer and the dynamic reputation management layer together constitute the supervision end in the first and second embodiments.

[0166] The business scenario collaboration processes that can be achieved through the core architecture include:

[0167] Scenario 1: Evidence Storage Process

[0168] 1. Trigger: A financial institution publishes or updates an H5 page;

[0169] 2. Fingerprint generation: The fingerprint generation engine calculates the composite hash, and the privacy-preserving proxy encrypts the transmission;

[0170] 3. On-chain registration: The smart contract interface calls the identity registration contract to store the digital fingerprint and initial reputation score;

[0171] 4. Feedback: Return the transaction receipt to the financial institution to complete the evidence storage.

[0172] Scenario 2: Verification Process

[0173] 1. Trigger: The monitoring system detects a suspicious page access request;

[0174] 2. Local verification: The edge node first queries the cached fingerprint library;

[0175] -Hit: directly return the verification result;

[0176] - Miss: Initiate on-chain zero-knowledge proof verification;

[0177] 3. On-chain verification: The zero-knowledge proof library verifies compliance, and the reputation scoring contract updates the score;

[0178] 4. Disposal decision: The risk decision module issues a ban / release instruction based on the score.

[0179] Scenario 3: Feedback Optimization Process

[0180] 1. Data analysis: The behavior analyzer collects statistics on recent verification logs and identifies abnormal patterns (for example, multiple verifications in a short period of time, multiple page updates in a short period of time, etc.);

[0181] 2. Threshold adjustment: The threshold adaptive module calculates the new threshold parameters;

[0182] 3. Strategy synchronization: Push the new threshold to the regulatory risk decision module;

[0183] 4. Rule updates: Cross-chain oracles synchronize the latest threat intelligence to the blockchain.

[0184] Taking the H5 page evidence storage and regulatory verification of financial institutions as an example, the specific implementation process is explained:

[0185] 1. Scene Background

[0186] -Financial institutions: A bank launched an H5 page for a wealth management product and needed to ensure the page content was compliant and prevent it from being mistakenly blocked.

[0187] -Regulatory authorities: It has been detected that this page has been visited multiple times and its legitimacy needs to be verified.

[0188] 2. Implementation steps

[0189] Step 1: Page Evidence

[0190] 1). Page publishing:

[0191] -The bank publishes an H5 page for its wealth management products, which includes product introductions, risk warnings, etc.

[0192] 2) Generate digital fingerprint:

[0193] -The fingerprint generation engine calculates the page hash:

[0194] -Input: page content + timestamp + random number

[0195] - Output: 256-bit hash value H = 0x891f...

[0196] 3) On-chain registration:

[0197] -Call the smart contract interface to register the digital fingerprint H to the blockchain.

[0198] Step 2: Regulatory Verification

[0199] 1) Detection access:

[0200] -The regulatory authorities detected that the page was accessed multiple times and extracted the current page hash H′=0xabcd... (which is different from the H=0x891f... stored on the chain).

[0201] 2) Edge Node Verification:

[0202] -Edge nodes query local cache:

[0203] -Miss: Initiate on-chain zero-knowledge proof verification.

[0204] 3) Zero-knowledge proof verification:

[0205] -The supervisory node calls the verification function, and the verification result Verify(CRS,π)=0 (failed).

[0206] 4) Update your reputation score:

[0207] -The reputation scoring contract updates the score based on the verification results:

[0208] - Rating before update: Pprior=0.8

[0209] -Updated rating:

[0210] 5) Disposal Decision:

[0211] -The risk decision module decides to immediately block the page based on the score Pnew = 0.3 and notifies the bank.

[0212] Step 3: Dynamic Adjustment

[0213] 1). Behavioral analysis:

[0214] -The behavior analyzer counts recent verification logs and finds that the page content has been tampered with and is marked as high risk.

[0215] 2) Threshold adjustment:

[0216] -Threshold adaptation module calculates new threshold:

[0217] -Base threshold: θ base =0.6

[0218] -Risk event: ∑RiskEvent24h=1

[0219] -Total verification events: Ntotal = 1000

[0220] - New thresholds:

[0221] 3. Implementation Effect

[0222] 1. Anti-missealing:

[0223] -The page was correctly blocked due to content tampering, preventing further risk from spreading.

[0224] 2. Privacy protection:

[0225] -Regulatory authorities do not obtain the specific content of the page, but only verify compliance.

[0226] 3. Efficient verification:

[0227] -Edge node cache miss, on-chain verification delay ≤ 150ms.

[0228] The fourth embodiment of the present disclosure also provides a domain name anti-misblocking system based on blockchain, the system includes the page to which the organization belongs, such as Figure 4 As shown, the organizations to which the page belongs include:

[0229] Monitoring module 11, which is configured to monitor new and updated events of pages in real time;

[0230] A generation module 12 is configured to generate a digital fingerprint for a page using a composite hash algorithm by collaboratively calculating a timestamp and a current reputation score of the organization to which the page belongs if the monitoring module monitors that a change in the page content exceeds a threshold;

[0231] The on-chain module 13 is configured to call the smart contract interface to register the digital fingerprint, the corresponding timestamp and the reputation score of the organization to which the current page belongs to the blockchain; so that when the regulatory end performs page detection, the hash value of the current page is extracted according to the same composite hash algorithm, and the current page is verified according to the extracted hash value and the digital fingerprint of the page to obtain a verification result, and the reputation score of the organization to which the page belongs is dynamically updated according to the verification result, and the page disposal strategy is determined according to the reputation score to dispose of the page.

[0232] Furthermore, the current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including:

[0233] Query the local cache at the edge computing node to see if the digital fingerprint of the current page is stored;

[0234] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0235] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0236] Furthermore, the generating module 12 is specifically configured as follows:

[0237] Generate a unique and irreversible digital fingerprint for the page through the core algorithm: H = SHA3-256 (C||T||[P*100]||Nonce);

[0238] Among them, C is the complete content of the H5 page, T is the current timestamp, P is the current reputation score of the organization to which the page belongs, and Nonce is a random number.

[0239] Furthermore, the generating module 12 is further configured to:

[0240] In the process of generating digital fingerprints, sensitive data processing is completed in the trusted execution environment TEE, the original page content is isolated, and based on Intel SGX technology, the memory data is fully encrypted.

[0241] The fifth embodiment of the present disclosure also provides a domain name anti-mistaken blocking system based on blockchain, the system includes a supervisory end, such as Figure 5 As shown, the supervisory end includes:

[0242] An extraction module 21 is configured to extract the hash value of the current page using a composite hash algorithm when performing page detection;

[0243] Verification module 22 is configured to verify the current page based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is generated by the page's organization by monitoring the addition and update events of the page in real time. When the page content changes exceeding a threshold, the same composite hash algorithm is used to collaboratively calculate the timestamp and the current reputation score of the page's organization. The page's organization calls the smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the current page's organization on the blockchain;

[0244] A rating update module 23, which is configured to dynamically update the reputation rating of the institution to which the page belongs based on the verification results;

[0245] The handling module 24 is configured to determine a page handling strategy based on the reputation score and handle the page.

[0246] Furthermore, the verification module 22 is specifically configured to:

[0247] Query the local cache at the edge computing node to see if the digital fingerprint of the current page is stored;

[0248] If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result;

[0249] If not, a zero-knowledge proof verification is initiated on the chain, so that the blockchain regulatory node calls the zero-knowledge proof verification function, verifies the current page, and returns the verification result.

[0250] Furthermore, the score updating module 23 is specifically configured as follows:

[0251] The reputation score is dynamically updated based on the verification results using the following formula:

[0252]

[0253] Among them, P prior is the current reputation score, P newIs the updated credit score.

[0254] Furthermore, the supervision end further includes an edge storage module 25;

[0255] The edge storage module 25 is configured to select digital fingerprints of frequently accessed and high-credit-value pages cached in the edge computing node through the following formula;

[0256] CachePriority = α * access frequency + β * P

[0257] Where CachePriority is the cache score of the page, the higher the score, the greater the cache probability, α and β are adjustable weights, and P is the credit score; and,

[0258] Use the LRU cache eviction policy algorithm to store the active digital fingerprints within a preset time.

[0259] Furthermore, the disposal module 24 is specifically configured as:

[0260] If the credit score ≥ 0.9, then automatically release;

[0261] If the credit score satisfies: Q ≤ credit score < 0.9, then conduct a manual review of the page;

[0262] If the credit score < Q, then immediately ban;

[0263] Where Q is the determination threshold and is dynamically adjusted according to the global risk situation.

[0264] Furthermore, the supervision end further includes an adjustment module 26;

[0265] The adjustment module 26 is configured to dynamically adjust the determination threshold according to the global risk situation, and the calculation formula is:

[0266]

[0267] Where θ(t) is the dynamically adjusted determination threshold, range: 0.0 - 1.0, θ base is the basic determination threshold, k is the adjustment coefficient, ∑RiskEvent 24h is the total number of risk events in the past 24 hours, and Ntotal is the total number of verification events in the past 24 hours.

[0268] Furthermore, the verification module 22 is specifically configured as:

[0269] Call the following zero-knowledge proof verification function to verify the compliance of the page:

[0270] π=Prove(CRS,(H,Sig),ComplianceRules)

[0271] Verify(CRS,π)→{0,1}

[0272] Among them, π is zero-knowledge proof, CRS is the public reference string, H is the page digital fingerprint, Sig is the institutional signature, and ComplianceRules is the compliance rules. The rule sets of different time periods are dynamically loaded through smart contracts to achieve the temporal and spatial adaptability of compliance verification.

[0273] The blockchain-based domain name anti-misblocking system of the disclosed embodiment is used to implement the blockchain-based domain name anti-misblocking method in method embodiments 1 to 3, so the description is relatively simple. For details, please refer to the relevant description in the previous method embodiments, which will not be repeated here.

[0274] In addition, if Figure 6 As shown, embodiment six of the present disclosure further provides an electronic device, including a memory 100 and a processor 200, wherein the memory 100 stores a computer program. When the processor 200 runs the computer program stored in the memory 100, the processor 200 executes the above-mentioned various possible methods.

[0275] The memory 100 is connected to the processor 200 . The memory 100 may be a flash memory, a read-only memory, or other memory. The processor 200 may be a central processing unit or a single-chip microcomputer.

[0276] In addition, an embodiment of the present disclosure further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is used by a processor to execute the above-mentioned various possible methods.

[0277] The computer-readable storage medium includes volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0278] It is understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present disclosure, and the present disclosure is not limited thereto. Those skilled in the art may make various modifications and improvements without departing from the spirit and substance of the present disclosure, and such modifications and improvements are also considered to be within the scope of protection of the present disclosure.

Claims

1. A method for preventing mis-blocking of domain names based on blockchain, characterized in that: The method comprises: The organization to which the page belongs monitors the page's new addition and update events in real time; If the page content changes exceeding the threshold, a composite hash algorithm is used to generate a digital fingerprint for the page by collaboratively calculating the timestamp and the current reputation score of the organization to which the page belongs. The smart contract interface is called to register the digital fingerprint, the corresponding timestamp and the reputation score of the organization to which the current page belongs to the blockchain; so that when the regulatory end performs page detection, the hash value of the current page is extracted according to the same composite hash algorithm, and the current page is verified according to the extracted hash value and the digital fingerprint of the page to obtain a verification result, and the reputation score of the organization to which the page belongs is dynamically updated according to the verification result, and the page disposal strategy is determined according to the reputation score to dispose of the page.

2. The method according to claim 1, characterized in that The current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including: Query the local cache at the edge computing node to see if the digital fingerprint of the current page is stored; If yes, verify the current page based on the extracted hash value and the digital fingerprint, and obtain the verification result; If not, a zero-knowledge proof verification is initiated on the chain, causing the blockchain regulatory node to call the zero-knowledge proof verification function, verify the current page, and return the verification result.

3. The method according to claim 2, characterized in that The method of using a composite hash algorithm to generate a digital fingerprint for a page by collaboratively calculating a timestamp and a current reputation score of the organization to which the page belongs includes: Generate a unique and irreversible digital fingerprint for the page through the core algorithm: H = SHA3-256 (C||T||[P*100]||Nonce); Among them, C is the complete content of the H5 page, T is the current timestamp, P is the current reputation score of the organization to which the page belongs, and Nonce is a random number.

4. The method according to claim 1, wherein The method further comprises: In the process of generating digital fingerprints, sensitive data processing is completed in the trusted execution environment TEE, the original page content is isolated, and based on Intel Software Guard Extensions Intel SGX technology, memory data is fully encrypted.

5. A method for preventing domain name from being blocked by mistake based on blockchain, characterized in that: The method comprises: When the supervisory end performs page detection, it extracts the hash value of the current page through a composite hash algorithm; The current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is monitored by the page's organization in real time for new and updated events. When the page content changes exceeding a threshold, the same composite hash algorithm is used to generate a page through collaborative calculation of the timestamp and the current reputation score of the page's organization. The page's organization calls the smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the current page's organization on the blockchain; Dynamically update the reputation score of the organization to which the page belongs based on the verification results; Determine the page handling strategy based on the reputation score and handle the page.

6. The method according to claim 5, characterized in that The current page is verified based on the extracted hash value and the digital fingerprint of the page to obtain a verification result, including: Query the local cache at the edge computing node to see if the digital fingerprint of the current page is stored; If so, verify the current page according to the extracted hash value and the digital fingerprint, and obtain a verification result; If not, initiate an on-chain zero-knowledge proof verification, enabling the blockchain regulatory node to call the zero-knowledge proof verification function to verify the current page and return the verification result.

7. The method according to claim 5, characterized in that Dynamically updating the reputation score of the organization to which the page belongs according to the verification result includes: Dynamically updating the reputation score according to the verification result through the following formula. The calculation formula is: Among them, P prior is the current reputation score, P new This is the updated reputation score.

8. The method according to claim 6, characterized in that The method further includes: Select the digital fingerprints of frequently accessed and high-reputation pages cached in the edge computing node through the following formula; CachePriority = α * access frequency + β * P Where CachePriority is the cache score of the page. The higher the score, the greater the cache probability. α and β are adjustable weights, and P is the reputation score; and, Use the least recently used (LRU) cache eviction policy algorithm to store the active digital fingerprints within a preset time.

9. The method according to claim 5, characterized in that Determining the page handling strategy according to the reputation score includes: If the reputation score ≥ 0.9, automatically release; If the reputation score satisfies: Q ≤ reputation score < 0.9, manually review the page; If the reputation score < Q, immediately ban; Where Q is the determination threshold, and it is dynamically adjusted according to the global risk situation.

10. The method according to claim 9, characterized in that The method further includes: Dynamically adjusting the determination threshold according to the global risk situation. The calculation formula is: Among them, θ(t) is the dynamically adjusted judgment threshold, ranging from 0.0 to 1.0, θ base is the basic judgment threshold, k is the adjustment coefficient, ∑RiskEvent 24h is the total number of risk events in the past 24 hours, and Ntotal is the total number of verification events in the past 24 hours.

11. The method according to claim 6, characterized in that Calling the zero-knowledge proof verification function to verify the current page includes: Call the following zero-knowledge proof verification function to verify the compliance of the page: π = Prove(CRS, (H, Sig), ComplianceRules) Verify(CRS, π) → {0, 1} Where π is the zero-knowledge proof, CRS is the common reference string, H is the page digital fingerprint, Sig is the organization signature, and ComplianceRules is the compliance rule. Different rule sets for different time periods are dynamically loaded through smart contracts to achieve the spatio-temporal adaptability of compliance verification.

12. A blockchain-based domain name anti-mistaken blocking system, characterized by: The system includes the organization to which the page belongs. The organization to which the page belongs includes: A listening module, which is set to listen for new and updated events of the page in real time; A generating module, which is set to use a composite hash algorithm to jointly calculate the digital fingerprint of the page through the time stamp and the current reputation score of the organization to which the page belongs if the listening module detects that the page content change exceeds the threshold; An on-chain module, which is set to call the smart contract interface to register the digital fingerprint, the corresponding time stamp, and the reputation score of the current organization to which the page belongs to the blockchain; so that when the regulatory side conducts page detection, it extracts the hash value of the current page according to the same composite hash algorithm, verifies the current page according to the extracted hash value and the digital fingerprint of the page, obtains the verification result, and dynamically updates the reputation score of the organization to which the page belongs according to the verification result, and determines the page handling strategy according to the reputation score to handle the page.

13. A blockchain-based domain name anti-mistaken blocking system, characterized by: The system includes a regulatory side. The regulatory side includes: An extraction module, which is set to extract the hash value of the current page through a composite hash algorithm when conducting page detection; A verification module is configured to verify the current page based on the extracted hash value and the digital fingerprint of the page to obtain a verification result. The digital fingerprint is generated by the organization to which the page belongs by monitoring the addition and update events of the page in real time. When the page content changes exceeding a threshold, the same composite hash algorithm is used to collaboratively calculate the timestamp and the current reputation score of the organization to which the page belongs. The organization to which the page belongs calls a smart contract interface to register the digital fingerprint, the corresponding timestamp, and the reputation score of the organization to which the current page belongs on the blockchain; A rating update module, which is configured to dynamically update the reputation score of the organization to which the page belongs based on the verification results; The disposal module is configured to determine a page disposal strategy based on the reputation score and to dispose of the page.

14. An electronic device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes the blockchain-based domain name anti-misblocking method as described in any one of claims 1 to 4 or claims 5 to 11.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the blockchain-based domain name anti-misblocking method as described in any one of claims 1-4 or claims 5-11.

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