Context-sec: Balancing Energy Consumption and Security of Mobile Devices

Abstract

Energy Management is of primary importance in mobile devices due to increasing functionality coupled with rapid battery drain. Research analysis reveals that users differ in context and resource usage patterns, which can be leveraged for power savings. A key challenge lies in providing context-adaptive security in an energy aware manner due to increasing sensitivity of user data and analyzing energy-security trade-offs. Towards this challenge, we model the problem of context-adaptive energy-aware security as a combinatorial optimization problem (Context-Sec). We then prove the decision version of this problem to be NP-Complete via a reduction from a variant of the well known Knapsack problem. We then design three different algorithms to solve a relaxed offline version of Context-Sec. The first algorithm is a pseudo-polynomial dynamic programming (DP) algorithm that computes an allocation with optimal user benefit using recurrence relations. The second algorithm is a greedy heuristic for allocation of security levels based on user benefit per unit of power consumption for each level. Finally, the third algorithm is a Fully Polynomial Time Approximation Scheme (FPTAS) for the problem which is has a polynomial time execution complexity as opposed to the pseudo-polynomial DP based approach. We subsequently implement and test the three algorithms on a real-world smartphone usage and wireless networks data-set to compare their performances. To the best of our knowledge, this is the first work that is focused on modeling, design, implementation and experimental performance analysis of any algorithm for context-adaptive energy-aware security. We believe our results will be useful for researchers and practitioners working in this area.