Feedback-based smartphone strategic sampling for BYOD security

Abstract

Bring Your Own Device (BYOD) is an information technology (IT) policy that allows employees to use their own wireless devices to access internal network at work. Mobile malware is a major security concern that impedes BYOD's further adoption in enterprises. Existing works identify the need for better BYOD security mechanisms that balance between the strength of such mechanisms and the costs of implementing such mechanisms. In this paper, based on the idea of self-reinforced feedback loop, we propose a periodic smartphone sampling mechanism that significantly improve BYOD security mechanism's effectiveness without incurring further costs. We quantify the likelihood that “a BYOD smartphone is infected by malware” by two metrics, vulnerability and uncertainty, and base the iterative sampling process on these two metrics; the updated values of these metrics are fed back into future rounds of the mechanism to complete the feedback loop. We validate the efficiency and effectiveness of the proposed strategic sampling via simulations driven by publicly available, real-world collected traces.