Blockchain-Based Multi-factor K-Anonymity Group Location Privacy Protection Scheme

Nowadays, location privacy issues have become an important problem faced by users of location-based services (LBS). For a long time, most researchers have focused on the location privacy protection of individual users and ignored the location privacy of group users, who will work together to complete an LBS task through collaborative computing. A small number of existing researchers have applied k-anonymity techniques to group location privacy protection, but the single use of k-anonymity techniques still suffers from malicious users providing fake location information, which can lead to the leakage of other users’ location information. To solve this problem, this paper proposes a blockchain-based multi-factor k-anonymity group location privacy protection scheme: first, this scheme proposes three factors: entity integrity, location trustworthiness and reputation penalty, fully considers the problem of reputation swing, gives the corresponding calculation scheme, and calculates the user reputation value based on these three factors; second, in the process of k-anonymity zone construction k-anonymous area is constructed by selecting users with high reputation values; finally, this scheme uses blockchain to store users’ reputation values and designs reputation calculation contracts to automatically calculate and update users’ reputation values. Security and experimental analysis prove that this scheme can effectively reduce the problem of malicious users providing fake location information and reputation swing, and can effectively resist collusion attacks and knowledge background attacks.