On-chain approximate nearest neighbor data privacy retrieval method and system based on locality sensitive hashing

• Main Authors: SHANG SIYUAN, LIU AODI, SHAN DIBIN, REN ZHIYU, WANG NA, WANG XIAOHAN, DU XUEHUI, WANG WENJUAN, CAO LIFENG
• Format: Patent
• Language: Chinese; English
• Published: 07.01.2025
• Subjects: CALCULATING; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

The invention relates to the technical field of block chain data management, in particular to an on-chain approximate nearest neighbor data privacy retrieval method and system based on locality sensitive hashing. A data management node obtains data from a chain and constructs a hash table for the on-chain data by using locality sensitive hashing; encrypting the hash table into a ciphertext by using attribute-based encryption according to an access control strategy, and storing and chaining the ciphertext; and acquiring the ciphertext under the condition that the access control strategy is met, and performing on-chain data retrieval on the retrieval vector by using the smart contract to acquire on-chain data most similar to the retrieval vector. According to the method, the local sensitive hashing technology and the distributed point function are used, the private information retrieval thought and the local sensitive hashing are combined to achieve approximate nearest neighbor retrieval of the on-chain data, f