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Title: Privacy-Enhancing Preferential LBS Query for Mobile Social Network Users
While social networking sites gain massive popularity for their friendship networks, user privacy issues arise due to the incorporation of location-based services (LBS) into the system. Preferential LBS takes a user’s social profile along with their location to generate personalized recommender systems. With the availability of the user’s profile and location history, we often reveal sensitive information to unwanted parties. Hence, providing location privacy to such preferential LBS requests has become crucial. However, the current technologies focus on anonymizing the location through granularity generalization. Such systems, although provides the required privacy, come at the cost of losing accurate recommendations. Hence, in this paper, we propose a novel location privacy-preserving mechanism that provides location privacy through k -anonymity and provides the most accurate results. Experimental results that focus on mobile users and context-aware LBS requests prove that the proposed method performs superior to the existing methods.  more » « less
Award ID(s):
1741277 1741338
PAR ID:
10212859
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Wireless Communications and Mobile Computing
Volume:
2020
ISSN:
1530-8669
Page Range / eLocation ID:
1 to 13
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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