An Efficient Context-Aware Privacy Preserving Approach for Smartphones. (27th April 2017)

• Record Type: Journal Article
• Authors: Zhang, Lichen; Li, Yingshu; Wang, Liang; Lu, Junling; Li, Peng; Wang, Xiaoming
• Other Names: Yang Qing Academic Editor.
• Is Part Of: Security and communication networks. Volume 2017(2017)
• Publication Date: 2017-04-27
• Subjects: Computer networks -- Security measures -- Periodicals; Computer security -- Periodicals; Cryptography -- Periodicals; 005.805
• DOI: 10.1155/2017/4842694
• Languages: English
• ISSNs: 1939-0114

Abstract

Abstract : With the proliferation of smartphones and the usage of the smartphone apps, privacy preservation has become an important issue. The existing privacy preservation approaches for smartphones usually have less efficiency due to the absent consideration of the active defense policies and temporal correlations between contexts related to users. In this paper, through modeling the temporal correlations among contexts, we formalize the privacy preservation problem to an optimization problem and prove its correctness and the optimality through theoretical analysis. To further speed up the running time, we transform the original optimization problem to an approximate optimal problem, a linear programming problem. By resolving the linear programming problem, an efficient context-aware privacy preserving algorithm (CAPP) is designed, which adopts active defense policy and decides how to release the current context of a user to maximize the level of quality of service (QoS) of context-aware apps with privacy preservation. The conducted extensive simulations on real dataset demonstrate the improved performance of CAPP over other traditional approaches.