Name
Abstract | ||
|---|---|---|
Location-based services have been enduring a fast development for almost fifteen years. Due to the lack of proper privacy protection, especially in the early stage of the development, an enormous amount of user request records have been collected. This exposes potential threats to users' privacy as new contextual information can be extracted from such records. In this paper, we study query dependency which can be derived from users' request history, and investigate its impact on users' query privacy. To achieve our goal, we present an approach to compute the probability for a user to issue a query, by taking into account both user's query dependency and observed requests. We propose new metrics incorporating query dependency for query privacy, and adapt spatial generalisation algorithms in the literature to generate requests satisfying users' privacy requirements expressed in the new metrics. Through experiments, we evaluate the impact of query dependency on query privacy and show that our proposed metrics and algorithms are effective and efficient for practical applications. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2435349.2435354 | CODASPY |
Keywords | DocType | Citations |
privacy requirement,location-based service,user request record,observed request,new metrics,proper privacy protection,exploring dependency,query privacy,query privacy protection,query dependency,new contextual information,fast development,proposed metrics,dependency,metrics,probability,privacy,anonymity,location based services | Conference | 3 |
PageRank | References | Authors |
0.38 | 26 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xihui Chen | 1 | 92 | 7.22 |
| Jun Pang | 2 | 3 | 0.38 |