关键词: 位置隐私, 隐私保护, 语义多样性, 语义位置类型相似度

Abstract:

Aiming at the problem of semantic inference attack caused by not considering semantic information in the anonymous set constructed by K-anonymous method in location-based service, a semantic diversity location privacy protection method in road network environment is proposed. According to the number of user accesses in different semantic locations, the method uses Euclidean distance to select other semantic location types with similar characteristics to construct an optimal semantic location type set. According to the proportion of semantic locations belonging to this type of set, the optimal segment is chosen to construct the anonymous set, which not only satisfies the semantic diversity, but also increases the uncertainty of users’ semantic location. The experimental results show that compared with the LSBASC algorithm, the method improves the average anonymous time by 27%, and the SDA algorithm performs better. The relative spatial granularity has decreased by 21%, and the privacy leakage has been reduced by 3%. That is, the SDA algorithm provides higher quality of service and privacy protection with a smaller anonymous space, and can effectively protect users’ semantic location privacy.

Key words: location privacy, privacy protection, semantic diversity, semantic location type similarity