Abstract
Recently, location based services (LBSs) have become increasingly popular due to advances in mobile devices and their positioning capabilities. In an LBS, the user sends a range of queries regarding his k-nearest neighbors (kNNs) that have common points of interests (POIs) based on his real geographic location. During the query sending, processing, and responding phases, private information may be collected by an attacker, either by tracking the real locations or by analyzing the sent queries. This compromises the privacy of the user and risks his/her safety in certain cases. Thus, the objective of this paper is to ensure comprehensive privacy protection, while also guaranteeing the efficiency of kNN query processing. Therefore, we propose an agent-based system for dealing with these issues. The system is managed by three software agents (selectorDL, fragmentorQ, and predictor). The selectorDL agent executes a Wise Dummy Selection Location (WDSL) algorithm to ensure the location privacy. The mission of the selectorDL agent is integrated with the mission of the fragmentorQ agent, which is to ensure the query privacy based on Left-Right Fragmentation (LRF) algorithm. To guarantee the efficiency of kNN processing, the predictor agent executes a prediction phase depending on a Cell Based Indexing (CBI) technique. Compared to similar privacy protection approaches, the proposed WDSL and LRF approaches showed higher resistance against location homogeneity attacks and query sampling attacks. In addition, the proposed CBI indexing technique obtains more accurate answers to kNN queries than the previous indexing techniques.
Highlights
Location Based Services (LBSs) are services that are customized according to the location of the user
The Global Positioning System (GPS), which is integrated with the mobile devices of the LBS users, allows the users to obtain their locations from the satellite and send them to the LBS server
In the context of fragmentation, we address the sensitive units of the query and the sensitive associations among the units because the attacker focuses on either one unit or the associations among two or more units to infer personal information
Summary
Location Based Services (LBSs) are services that are customized according to the location of the user. The LBS server processes the query and sends back the results This classical scenario involves risk since the LBS user is forced to construct the query based on his/her real geographic location. Some inference attacks, such as location homogeneity attack [14] (which targets location privacy) and query analysis attack, such as query sampling attack [15] (which targets query privacy), can be applied by an attacker to circumvent the privacy protection methods In both inference attacks and query analysis attacks, the attacker does not need to know the accurate location of the LBS user to infer the personal data. The main contributions of this work are as follows: To protect the location privacy of LBS users, we introduce a novel Wise Dummy Selection Location (WSDL) algorithm.
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