PPVC: Privacy Preserving Voronoi Cell for location-based services

A Collaboration‐Based Scheme for Location‐Based Services with Incentive Mechanism

“…Location perturbation and obfuscation technique [11−14] adds some noise to the real location, then expands the query region to ensure the quality of service. Spatial and temporal cloaking technique [9,10] generates a suitable cloaking area including at least k − 1 users. Dummy location technique [3,15,16] generates dummies and submits them with the real one to the LBS server.…”

“…To address these privacy issues, many approaches [1−6] have been proposed to protect location privacy in literature. Besides policy-based solutions and cryptography primitive-based approaches [7,8] , there are several nonencryption techniques, such as spatial cloaking [9,10] , location perturbation and obfuscation [11−14] , and dummy location [3,15,16] . These methods are widely used because their computation overhead is much smaller than cryptography primitive-based approaches.…”

Delay‐aware privacy‐preserving location‐based services under spatiotemporal constraints

“… Many of the existing obfuscation techniques generate CRs at random, without considering any prior related to the user 7,9 . Thus, from a given random CR 0 , an adversary with information 1 can exclude some locations (the dark regions in Figure 1a) for having very low probability to be the user's location and finds a smaller region, . The majority of the methods focus on a single query and fail to provide privacy for multiple queries.…”

“…Another category of user-centric approaches is the disclosure of locations with reduced precision, called location obfuscation. [7][8][9][10] The idea is to replace a user's precise location information with a larger region called the concealing region (CR), with a compromise of quality-of-service (QoS). Unlike many other approaches, through methodical design, obfuscation approaches can be implemented in various applications, including real-time navigation, POI search, and social network check-ins.…”

UMBRELLA: user demand privacy preserving framework based on association rules and differential privacy in social networks

“…On the other hand, location trajectories can excavate more sensitive information despite location. In this regard, location privacy-preserving mechanisms have been extensively studied, such as Dummy, spatial confusion [3,4], encryption technology [5,6], differential privacy (DP) [7,8] and references therein.…”