Research on Co-Location Privacy-Preserving System

Li, Jiachun; Xiong, Dongqing; Cao, Jianzhou

doi:10.1109/msn.2018.00030

Cited by 1 publication

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Considering the impact of the environment on location privacy when the system is threatened, [23] proposes a new location privacy metric related to the surrounding environment, and a stochastic model that can capture spatial changes along the user path, and develops a new stop-based best LBS access scheme. [24] proposed a co-location privacypreserving system framework, the key technologies of the system is location privacy-preserving agent. It defines novel calculation method of relation strength based on bi-direction interaction frequency between user and friends, and designs two algorithms based on user's coordination and co-location information concealment and time adjustment which is suitable for different location privacy-preserving scenarios, but It uses a centralized location protection method that is vulnerable to malicious attacks by attackers.…”

Section: Related Workmentioning

confidence: 99%

Service Recommendation Middleware Based on Location Privacy Protection in VANET

2020

View full text Add to dashboard Cite

With the help of location-based services (LBS), it makes driving more convience for drivers. However, because the untrusted LBS server may leak the user's location information, the user's privacy is threatened. Moreover, the existing methods of location privacy protection do not take into account the impact of context on privacy protection demand. In addition, heterogeneous data sensed by vehicles also increases the complexity of application development. In order to solve the above problems, we propose a context-based location privacy protection middleware architecture, named PP-OSGi. The middleware simplifies application development by shielding the heterogeneity of vehicle sensed data and upper-layer applications. Furthermore, in order to protect the real location information of service request vehicles under different vehicle densities in a certain area, we propose a dynamically adjustable k-anonymous (DAK) algorithm and a location privacy protection (DLP) algorithm based on a dummy location, which are all encapsulated in PP-OSGi. The DAK and DLP algorithms dynamically determine the location privacy protection strength in different contexts based on the user's location privacy preference model, select an anonymous group of neighboring vehicles to construct a anonymous area, and obtain a dummy location of the service request vehicle. The experimental results show that, under the premise of protecting the location privacy of vehicles, the success rate of service requests is improved and the communication cost between vehicles is reduced.

show abstract

Section: Related Workmentioning

confidence: 99%