Supply chain collaborative management method and system based on anti-counterfeiting code

Abstract

The invention relates to the technical field of anti-counterfeiting codes, in particular to a supply chain collaborative management method and system based on an anti-counterfeiting code, and the method comprises the following steps: 1, carrying out the multi-layer encryption of the anti-counterfeiting code: designing the anti-counterfeiting code through employing static anti-counterfeiting and dynamic anti-counterfeiting, limiting the length of the anti-counterfeiting code according to the needs of a product, and carrying out the multi-layer encryption of the anti-counterfeiting code; the anti-counterfeiting code is encrypted by combining multiple anti-counterfeiting technologies of hash encryption, timestamp and watermark anti-counterfeiting, and the encrypted anti-counterfeiting code corresponds to a unique product and is stored in a block chain account book; 2, block chain evidence storage: recording production, storage, logistics and sales nodes of the product, setting an intelligent contract, and binding a geographic position in combination with GPS and base station data; according to the method, the problem that an existing anti-counterfeiting code is prone to being copied and tampered is effectively solved by adopting the multi-layer encrypted anti-counterfeiting code design and the block chain evidence storage technology, and the uniqueness and irreversibility of the anti-counterfeiting code are ensured by combining the static anti-counterfeiting code with the dynamic anti-counterfeiting code and combining the Hash encryption technology, the timestamp technology, the watermark technology and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of anti-counterfeiting codes, and specifically to a supply chain collaborative management method and system based on anti-counterfeiting codes. Background Art

[0002] With the increasing complexity of the global supply chain, especially in the fields of high-value goods, consumer goods, and pharmaceutical products, the circulation of counterfeit and shoddy products has become a serious problem. Traditional anti-counterfeiting technologies mainly rely on single anti-counterfeiting labels or two-dimensional codes, but these technologies often have the risks of being copied, tampered with, or misused. Especially in the gray market, counterfeit products may circulate through unauthorized channels, resulting in damaged brand reputation, violated consumer rights, and even endangering public safety. In the prior art, although anti-counterfeiting codes can be generated and applied to products through methods such as two-dimensional codes, RFID, and NFC, they still face problems such as easy replication of anti-counterfeiting codes, information tampering, and circulation in the gray market. In particular, for large-scale supply chain management, how to ensure that each product can circulate through legal channels, prevent counterfeit and shoddy products from flowing into the market, and ensure the authenticity and reliability of product information. Therefore, in view of the above problems, a supply chain collaborative management method and system based on anti-counterfeiting codes are proposed. Summary of the Invention

[0003] The purpose of the present invention is to provide a supply chain collaborative management method and system based on anti-counterfeiting codes to solve the problem of how to ensure that each product can circulate through legal channels, prevent counterfeit and shoddy products from flowing into the market, and ensure the authenticity and reliability of product information for large-scale supply chain management.

[0004] To achieve the above purpose, the present invention provides the following technical solutions: A supply chain collaborative management method and system based on anti-counterfeiting codes, including the following steps: Step 1: Perform multi-layer encryption on the anti-counterfeiting code: Design the anti-counterfeiting code using a double-layer design of static anti-counterfeiting and dynamic anti-counterfeiting, limit the length of the anti-counterfeiting code according to product requirements, and encrypt the anti-counterfeiting code by combining multiple anti-counterfeiting technologies such as hash encryption, timestamp, and watermark anti-counterfeiting. After encryption, the anti-counterfeiting code corresponds to a unique product and is stored in the blockchain ledger. Step 2: Blockchain evidence storage: Record the production, warehousing, logistics, and sales nodes of the product, set up smart contracts, and bind the geographical location by combining GPS and base station data at the same time. Step 3: Combine the smart contract and the authorization system: Set the limited query times of the dynamic anti-counterfeiting code according to needs, and perform advanced anti-counterfeiting verification by combining face recognition and fingerprint recognition. Consumers can unlock the query permission of the anti-counterfeiting code by binding a mobile phone number or a social account, and the consumer query page provides incentives such as points and discounts. Distributors unlock products with corresponding permissions through anti-counterfeiting code authorization mechanisms at different levels, and combine with smart contracts to restrict unauthorized transfer of goods through illegal channels; Step 4: Combination of AI and big data analysis: Through RFID, NFC, and two-dimensional code technologies, conduct full-process visual tracking of logistics; And through AI and big data analysis, conduct intelligent monitoring of the inventory in each channel, detect abnormal query behaviors at the same time, trigger an early warning mechanism, and provide real-time data analysis reports for the situation where gray products flow into unauthorized areas; Step 5: Combination of dynamic anti-counterfeiting code and real-name query: After detecting abnormally circulated products, the anti-counterfeiting code is marked as a blacklist and subsequent queries are prohibited. The blacklist products trigger an intelligent risk control system to warn consumers and report to the brand side.

[0005] As a further optimized content of the present invention, wherein: the step of limiting the length of the anti-counterfeiting code according to the product needs includes the following steps: S1: Calculate the minimum length of anti-counterfeiting according to the product needs , the minimum length The calculation formula is: ; In the formula, is the number of products.

[0006] S2: Calculate the security requirements of the anti-counterfeiting code and add random security bits to the anti-counterfeiting code , the random security bits The calculation formula is: ; In the formula, is the cracking probability; determine the total length of the anti-counterfeiting code through the random security bits , the total length of the anti-counterfeiting code , the total length of the anti-counterfeiting code ; S3: Compress and store the anti-counterfeiting code in the Base32 or Base64 encoding format. When using Base32 encoding, the length of the anti-counterfeiting code is 13 characters, and when using Base64 encoding, the length of the anti-counterfeiting code is 11 characters.

[0007] As a further optimized content of the present invention, wherein: after detecting an abnormality in step 5, automatically execute restrictive measures, prohibit the product from being queried in a specific area and lock the inventory, and at the same time combine the blockchain traceability record to quickly track the source of the gray market circulation and provide judicial evidence collection support.

[0008] As a further optimized content of the present invention, it includes an anti-counterfeiting code, an anti-counterfeiting code generation and binding module, a full-process traceability management module for the supply chain, a supply chain collaborative management module, a consumer verification and anomaly detection module, and an intelligent risk control and anti-counterfeiting code traceability feedback module; The anti-counterfeiting code adopts a double-layer design of static anti-counterfeiting and dynamic anti-counterfeiting, and combines multiple anti-counterfeiting technologies such as hash encryption, timestamp, and watermark anti-counterfeiting; The anti-counterfeiting code generation and binding module uses a binding mechanism in which each anti-counterfeiting code uniquely corresponds to a product and is stored in the blockchain ledger to ensure the immutability of data; The full-process traceability management module for the supply chain is used for blockchain evidence storage, smart contracts, and geographical location binding; The supply chain collaborative management module includes a logistics tracking system, intelligent inventory monitoring, and dealer permission management; The consumer verification and anomaly detection module is used for dynamic anti-counterfeiting verification, consumer real-name authentication, and AI anomaly detection; The intelligent risk control and anti-counterfeiting code traceability feedback module includes an anti-counterfeiting code blacklist system and an intelligent contract automatic execution risk control strategy.

[0009] As a further optimized content of the present invention, the blockchain evidence storage uses the blockchain to record key nodes such as the production, warehousing, logistics, and sales of products to ensure the immutability of supply chain data; The smart contract sets a smart contract to ensure that products can only flow through authorized supply chain links; The geographical location binding combines GPS + base station data to ensure that products are only sold in authorized areas.

[0010] As a further optimized content of the present invention, the logistics tracking system combines RFID / NFC / QR code technology to achieve full-process visualization of logistics; The intelligent inventory monitoring monitors the inventory of each channel through AI + big data analysis to identify abnormal circulation behaviors; The dealer permission management adopts an anti-counterfeiting code authorization mechanism. Dealers at different levels can only unlock products with corresponding permissions, and in combination with smart contracts, it restricts unauthorized channel transfer and sales.

[0011] As a further optimized content of the present invention, the dynamic anti-counterfeiting code verification is such that the dynamic anti-counterfeiting code of each product can only be queried once or a limited number of queries are set, and at the same time, in combination with face recognition or fingerprint recognition, advanced anti-counterfeiting verification is carried out; The consumer real-name verification includes binding a mobile phone number or social account when querying the anti-counterfeiting code, and in combination with an intelligent recommendation system, providing incentives such as points and discounts to legitimate users; The AI anomaly detection uses big data analysis + AI models to detect abnormal query behaviors, trigger a warning mechanism, and at the same time provide real-time data analysis reports for the situation where gray market products flow into unauthorized areas.

[0012] As a further optimized content of the present invention, wherein: after the anti-counterfeiting code blacklist system discovers an abnormally circulated product, the anti-counterfeiting code is marked as a blacklist, and the blacklist product triggers the intelligent risk control system to warn consumers and report to the brand side; After the intelligent contract automatically executes the risk control strategy and discovers an anomaly, it automatically executes restrictive measures, and combines with the blockchain traceability record to quickly track the source of gray market circulation and provide judicial evidence collection support.

[0013] Compared with the prior art, the beneficial effects of the present invention are: 1. In the present invention, a multi-layer encrypted anti-counterfeiting code design and blockchain evidence storage technology are adopted, effectively solving the problems that existing anti-counterfeiting codes are easily copied and tampered with. The combination of static anti-counterfeiting codes and dynamic anti-counterfeiting codes, combined with technologies such as hash encryption, time stamps, and watermarks, ensures the uniqueness and irreversibility of anti-counterfeiting codes, and the immutability of the blockchain guarantees the authenticity of each product information and the integrity of data, greatly enhancing the security and anti-tampering ability of anti-counterfeiting codes; 2. In the present invention, the combination of intelligent contracts and geographical location binding solves the problem of gray market circulation. The setting of intelligent contracts enables products to only flow in authorized supply chain links, and through the combination of GPS and base station data, geographical location binding of products is achieved, ensuring that products are only sold in authorized areas, preventing cross-regional circulation or illegal transfer of goods, and this mechanism effectively avoids the risk of counterfeit and shoddy products flowing into the market through informal channels; 3. In the present invention, the introduction of AI and big data analysis further enhances the visualization and intelligent monitoring of the supply chain. The system can real-time monitor the inventory situation of each channel, identify abnormal query behaviors, and timely discover and respond to gray market circulated products through the warning mechanism. In addition, the combination of dynamic anti-counterfeiting codes and consumer real-name queries further improves the accuracy and effectiveness of anti-counterfeiting verification, ensuring that consumers can safely and conveniently query the authenticity of products, and at the same time promoting legal consumption behaviors through incentives such as points and discounts. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flowchart of the supply chain collaborative management method based on anti-counterfeiting codes of the present invention; Figure 2 is a system block diagram of the supply chain collaborative management system based on anti-counterfeiting codes of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] Please refer to Figure 1-2 , the present invention provides a technical solution: Anti-counterfeiting code-based supply chain collaborative management method and system, comprising the following steps: Step 1: Multilayer encryption of anti-counterfeiting codes: Design anti-counterfeiting codes using a dual-layer design of static anti-counterfeiting and dynamic anti-counterfeiting. Limit the length of the anti-counterfeiting code according to product requirements, and encrypt the anti-counterfeiting code by combining multiple anti-counterfeiting technologies such as hash encryption, timestamp, and watermark anti-counterfeiting. After encryption, map the anti-counterfeiting code to a unique product and store it in the blockchain ledger; Step 2: Blockchain evidence storage: Record the production, warehousing, logistics, and sales nodes of the product, and set up smart contracts. At the same time, bind the geographical location by combining GPS and base station data; Step 3: Combination of smart contracts and authorization systems: Set the limited number of queries for dynamic anti-counterfeiting codes as needed, and perform advanced anti-counterfeiting verification by combining face recognition and fingerprint recognition; Consumers can unlock the query permission by binding their mobile phone numbers or social accounts. The consumer query page provides incentives such as points and discounts; Distributors can unlock products with corresponding permissions through anti-counterfeiting code authorization mechanisms at different levels, and combine smart contracts to restrict unauthorized transfers through illegal channels; Step 4: Combination of AI and big data analysis: Through RFID, NFC, and two-dimensional code technologies, conduct full-process visual tracking of logistics; And through AI and big data analysis, intelligently monitor the inventory of each channel, detect abnormal query behaviors at the same time, and trigger an early warning mechanism. Provide real-time data analysis reports for the situation where gray products flow into unauthorized areas; Step 5: Combination of dynamic anti-counterfeiting codes and real-name queries: After discovering abnormally circulated products, the anti-counterfeiting code is marked as a blacklist and subsequent queries are prohibited. The blacklist products trigger the intelligent risk control system, warning consumers and reporting to the brand owner. Through multilayer encryption and blockchain evidence storage, the security and immutability of the anti-counterfeiting code are improved. At the same time, the transparency and monitoring capabilities of the supply chain are strengthened by using smart contracts, AI, and big data analysis, effectively preventing the circulation in the gray market and the entry of counterfeit products.

[0016] As a further implementation technical solution of this scheme, limiting the length of the anti-counterfeiting code according to product requirements in Step 1 includes the following steps: S1: Calculate the minimum length of anti-counterfeiting according to product requirements , and the minimum length The calculation formula is: ; In the formula, is the number of products.

[0017] S2: Calculate the security requirements of the anti-counterfeiting code and add random security bits to the anti-counterfeiting code , and the random security bits The calculation formula is as follows: ; In the formula, is the cracking probability; the total length of the anti-counterfeiting code is determined by random secure bits , and the total length of the anti-counterfeiting code is ; ; S3: Compress and store the anti-counterfeiting code in the Base32 or Base64 encoding format. When using Base32 encoding, the length of the anti-counterfeiting code is 13 characters, and when using Base64 encoding, the length of the anti-counterfeiting code is 11 characters. By precisely calculating the minimum length and security requirements of the anti-counterfeiting code, it is ensured that the anti-counterfeiting code can not only guarantee high security but also adapt to the needs of different products. At the same time, compressed storage optimizes the query and management efficiency; As a further technical solution for the implementation of this scheme, after an anomaly is detected in step five, restriction measures are automatically executed to prohibit product queries in specific regions and lock the inventory. At the same time, combined with the blockchain traceability record, the source of the gray market circulation can be quickly traced, providing support for judicial evidence collection. By automatically restricting and locking abnormally circulating products and combining blockchain traceability records, the traceability efficiency and accuracy are improved, the system's prevention ability against the gray market is enhanced, and effective evidence support is provided for legal litigation; As a further technical solution for the implementation of this scheme, it includes an anti-counterfeiting code, an anti-counterfeiting code generation and binding module, a full-process traceability management module for the supply chain, a supply chain collaborative management module, a consumer verification and anomaly detection module, and an intelligent risk control and anti-counterfeiting code traceability feedback module; The anti-counterfeiting code adopts a dual-layer design of static anti-counterfeiting and dynamic anti-counterfeiting, and combines multiple anti-counterfeiting technologies such as hash encryption, timestamp, and watermark anti-counterfeiting; The anti-counterfeiting code generation and binding module uses a binding mechanism in which each anti-counterfeiting code uniquely corresponds to a product and is stored in the blockchain ledger to ensure the immutability of data; The full-process traceability management module for the supply chain is used for blockchain evidence storage, smart contracts, and geographical location binding; The supply chain collaborative management module includes a logistics tracking system, intelligent inventory monitoring, and dealer permission management; The consumer verification and anomaly detection module is used for dynamic anti-counterfeiting verification, consumer real-name authentication, and AI anomaly detection; The intelligent risk control and anti-counterfeiting code traceability feedback module includes an anti-counterfeiting code blacklist system and a smart contract automatic execution risk control strategy, integrating anti-counterfeiting code generation, traceability, verification, and risk control, ensuring the integrity, transparency, and security of the supply chain, effectively combating forgery and gray market circulation, and improving the credibility of products; As a further technical solution for this solution, blockchain evidence storage uses the blockchain to record key nodes such as product production, warehousing, logistics, and sales to ensure the immutability of supply chain data; Smart contract Set up a smart contract to ensure that products can only be circulated in authorized supply chain links; Geographical location binding Combine GPS + base station data to ensure that products are only sold in authorized areas. Through blockchain evidence storage and smart contracts, the transparency and immutability of the supply chain process are ensured. Geographical location binding ensures that products are only sold in authorized areas, effectively preventing cross-regional forgery and gray market circulation; As a further technical solution for this solution, the logistics tracking system combines RFID / NFC / QR code technology to achieve full-process logistics visualization; Intelligent inventory monitoring uses AI + big data analysis to monitor the inventory of each channel and identify abnormal circulation behaviors; Dealer permission management adopts an anti-counterfeiting code authorization mechanism. Dealers at different levels can only unlock products with corresponding permissions. Combined with smart contracts, it restricts unauthorized transfer and sales through illegal channels. Through logistics tracking and intelligent inventory monitoring, the product flow and inventory situation can be grasped in real time. Combined with dealer permission management, it ensures that product circulation is limited to authorized channels and prevents forgery and illegal circulation; As a further technical solution for this solution, the dynamic anti-counterfeiting code verification means that the dynamic anti-counterfeiting code for each product can only be queried once or a limited number of queries can be set. At the same time, combined with face recognition or fingerprint recognition, advanced anti-counterfeiting verification is carried out; Consumer real-name verification includes binding a mobile phone number or social account when querying the anti-counterfeiting code, and combined with an intelligent recommendation system, providing incentives such as points and discounts to legitimate users; AI anomaly detection uses big data analysis + AI models to detect abnormal query behaviors and trigger an early warning mechanism. At the same time, in the case of gray market products flowing into unauthorized areas, a real-time data analysis report is provided. Through dynamic anti-counterfeiting code verification and consumer real-name verification, the security of the anti-counterfeiting code is enhanced. Combined with AI anomaly detection and intelligent recommendation systems, the user experience and anti-counterfeiting efficiency are improved, and the risk of gray market product inflows is reduced; As a further technical solution for this solution, after an abnormal circulation product is found in the anti-counterfeiting code blacklist system, the anti-counterfeiting code is marked as a blacklist, and the blacklist product triggers an intelligent risk control system to warn consumers and report to the brand owner; After the intelligent contract automatically executes the risk control strategy and discovers an anomaly, it automatically executes restrictive measures, and combines with the blockchain traceability record to quickly trace the source of the gray market circulation, providing judicial evidence collection support. The blacklist function and intelligent risk control strategy can take timely restrictive measures when abnormal circulation products are discovered, preventing illegal merchants from continuing to sell counterfeit products, and providing traceability and legal evidence collection support for brand owners, effectively reducing the circulation risk of counterfeit and shoddy products.

[0018] In this article, specific examples are used to elaborate on the principle and implementation method of the present invention. The description of the above examples is only used to help understand the method and its core idea of the present invention. The above is only the preferred implementation method of the present invention. It should be noted that due to the limitation of literal expression and objectively infinite specific structures, for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements, retouches or changes can be made, or the above technical features can be combined in an appropriate manner; these improvements, retouches, changes or combinations, or directly applying the concept and technical solution of the invention to other occasions without improvement, shall all be regarded as the protection scope of the present invention.

Claims

1. A supply chain collaborative management method based on anti-counterfeiting code, characterized in that: The following steps are involved: Step 1: Multi-layer encryption of the anti-counterfeiting code: The anti-counterfeiting code is designed with static anti-counterfeiting and dynamic anti-counterfeiting double layers. The length of the anti-counterfeiting code is limited according to product needs. The anti-counterfeiting code is encrypted by combining hash encryption, timestamp, and watermark anti-counterfeiting multiple anti-counterfeiting technologies. After encryption, the anti-counterfeiting code corresponds to a unique product and is stored in the blockchain account book; Step 2: Blockchain evidence storage: record the production, warehousing, logistics and sales nodes of the product, set up smart contracts, and bind the geographic location in combination with GPS and base station data; Step 3: Combination of smart contracts and authorization systems: Set the limited query times of dynamic anti-counterfeiting codes as needed, and combine face recognition and fingerprint recognition for advanced anti-counterfeiting verification; Consumers can unlock the query rights by binding their mobile phone number or social account to query the anti-counterfeiting code. The consumer query page provides points and discount incentives. Distributors unlock products with corresponding permissions through different levels of anti-counterfeiting code authorization mechanisms, and combine smart contracts to restrict illegal channels from transferring goods privately; Step 4: Combination of AI and big data analysis: Through RFID, NFC and QR code technology, the whole process of logistics can be visually tracked; Through AI and big data analysis, we can intelligently monitor the inventory of each channel, detect abnormal query behavior, trigger early warning mechanisms, and provide real-time data analysis reports for situations where gray products flow into unauthorized areas; Step 5: Combination of dynamic anti-counterfeiting code and real-name query: After discovering abnormally circulated products, the anti-counterfeiting code is marked as blacklisted and subsequent queries are prohibited. Blacklisted products trigger the intelligent risk control system, warning consumers and alerting the brand.

2. The supply chain collaborative management method based on anti-counterfeiting code according to claim 1 is characterized by: The step 1 in which the length of the anti-counterfeiting code is limited according to product requirements includes the following steps: S1: Calculate the minimum length of anti-counterfeiting according to product requirements , minimum length The calculation formula is: ； In the formula, is the product quantity; S2: Calculate the security requirements of the anti-counterfeiting code and add random security bits to the anti-counterfeiting code , the random security bit The calculation formula is: ； In the formula, For cracking probability; through random security bits Determine the total length of the security code , the total length of the security code ; S3: The anti-counterfeiting code is compressed and stored in Base32 or Base64 encoding format. The length of the anti-counterfeiting code is 13 characters when Base32 is encoded, and the length of the anti-counterfeiting code is 11 characters when Base64 is encoded.

3. The supply chain collaborative management method based on anti-counterfeiting code according to claim 1 is characterized by: When an anomaly is discovered in step five, restrictive measures are automatically implemented to prohibit product inquiries and lock inventory in specific areas. At the same time, combined with blockchain traceability records, the source of gray market circulation can be quickly tracked to provide judicial evidence support.

4. The supply chain collaborative management system based on anti-counterfeiting codes according to claim 1 is characterized in that: Including anti-counterfeiting code, anti-counterfeiting code generation and binding module, supply chain full-process traceability management module, supply chain collaborative management module, consumer verification and anomaly detection module, and intelligent risk control and anti-counterfeiting code traceability feedback module; The anti-counterfeiting code adopts a double-layer design of static anti-counterfeiting and dynamic anti-counterfeiting, and the anti-counterfeiting code combines multiple anti-counterfeiting technologies such as hash encryption, time stamp, and watermark anti-counterfeiting; The anti-counterfeiting code generation and binding module uses a binding mechanism that ensures that each anti-counterfeiting code uniquely corresponds to a product and is stored in a blockchain ledger to ensure that the data cannot be tampered with; The supply chain full-process traceability management module is used for blockchain evidence storage, smart contracts and geographic location binding; The supply chain collaborative management module includes logistics tracking system, inventory intelligent monitoring and dealer authority management; The consumer verification and anomaly detection module is used for dynamic anti-counterfeiting verification, consumer real-name authentication and AI anomaly detection; The intelligent risk control and anti-counterfeiting code traceability feedback module includes an anti-counterfeiting code blacklist system and a smart contract that automatically executes risk control strategies.

5. The supply chain collaborative management system based on anti-counterfeiting codes according to claim 1 is characterized by: The blockchain evidence storage uses blockchain to record key nodes such as production, warehousing, logistics, and sales of products to ensure that supply chain data cannot be tampered with; The smart contract sets up a smart contract to ensure that the product can only circulate in the authorized supply chain link; The geolocation binding combines GPS+base station data to ensure that products are only sold in authorized areas.

6. The supply chain collaborative management system based on anti-counterfeiting code according to claim 1 is characterized by: The logistics tracking system combines RFID / NFC / QR code technology to achieve visualization of the entire logistics process; The intelligent inventory monitoring uses AI + big data analysis to monitor the inventory of each channel and identify abnormal circulation behavior; The dealer authority management adopts an anti-counterfeiting code authorization mechanism. Dealers of different levels can only unlock products with corresponding permissions, and combined with smart contracts, it restricts illegal channels from privately transferring goods for sale.

7. The supply chain collaborative management system based on anti-counterfeiting codes according to claim 1 is characterized by: The dynamic anti-counterfeiting code verification is used for each product. The dynamic anti-counterfeiting code can only be queried once or a limited number of queries can be set. At the same time, it is combined with face recognition or fingerprint recognition to perform advanced anti-counterfeiting verification; The consumer real-name verification includes binding a mobile phone number or social account when querying the anti-counterfeiting code, and combining it with an intelligent recommendation system to provide incentives such as points and discounts to legitimate users; The AI ​​anomaly detection uses big data analysis + AI models to detect abnormal query behavior and trigger an early warning mechanism. At the same time, it provides real-time data analysis reports for the situation where gray market products flow into unauthorized areas.

8. The supply chain collaborative management system based on anti-counterfeiting codes according to claim 1 is characterized by: When the anti-counterfeiting code blacklist system finds abnormally circulated products, the anti-counterfeiting code is marked as blacklisted, and the blacklisted products trigger the intelligent risk control system to warn consumers and report to the brand; The smart contract automatically executes risk control strategies and automatically executes restrictive measures after discovering anomalies. It also combines blockchain traceability records to quickly track the source of gray market circulation and provide judicial evidence support.

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