A Differential Privacy Protection Protocol Based on Location Entropy

Abstract

A Location-Based Service (LBS) refers to geolocation-based services that bring both convenience and vulnerability. With an increase in the scale and value of data, most existing location privacy protection protocols cannot balance privacy and utility. To solve the revealing problems in LBS, we propose a differential privacy protection protocol based on location entropy. First, we design an algorithm of the best-Assisted user selection for constructing anonymity sets. Second, we employ smart contracts to evaluate the credibility of participants, which ensures the honesty of participants. Moreover, we provide a comprehensive experiment; the theoretical analysis and experiments show that the proposed protocol effectively resists background knowledge attacks. Generally, our protocol improves data availability. Particularly, it realizes user-controllable privacy protection, which improves privacy protection and strengthens security.