期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：10
页码：191-201
出版社：Science and Information Society (SAI)
摘要：In recent years, privacy has become great attention
in the research community. In Location-based Recommendation
Systems (LbRSs), the user is constrained to build queries depend
on his actual position to search for the closest points of interest
(POIs). An external attacker can analyze the sent queries or
track the actual position of the LbRS user to reveal his\her
personal information. Consequently, ensuring high privacy
protection (which is including location privacy and query
privacy) is a fundamental thing. In this paper, we propose a
model that guarantees high privacy protection for LbRS users.
The model is work by three components: The first component
(selector) uses a new location privacy protection approach,
namely, the smart dummy selection (SDS) approach. The SDS
approach generates a strong dummy position that has high
resistance versus a semantic position attack. The second
component (encryptor) uses an encryption-based approach that
guarantees a high level of query privacy versus a sampling query
attack. The last component (constructor) constructs the protected
query that is sent to the LbRS server. Our proposed model is
supported by a checkpoint technique to ensure a high availability
quality attribute. Our proposed model yields competitive results
compared to similar models under various privacy and
performance metrics.
