To refer to this page use:
|Abstract:||Smartphones are now frequently used by end-users as the portals to cloud-based services, and smartphones are easily stolen or co-opted by an attacker. Beyond the initial login mechanism, it is highly desirable to re-authenticate endusers who are continuing to access security-critical services and data, whether in the cloud or in the smartphone. But attackers who have gained access to a logged-in smartphone have no incentive to re-authenticate, so this must be done in an automatic, non-bypassable way. Hence, this paper proposes a novel authentication system, iAuth, for implicit, continuous authentication of the end-user based on his or her behavioral characteristics, by leveraging the sensors already ubiquitously built into smartphones. We design a system that gives accurate authentication using machine learning and sensor data from multiple mobile devices. Our system can achieve 92.1% authentication accuracy with negligible system overhead and less than 2% battery consumption.|
|Electronic Publication Date:||18-Jun-2016|
|Citation:||Lee, W-H, Lee, R. (2016). Implicit sensor-based authentication of smartphone users with smartwatch. 18-June-2016 (10.1145/2948618.2948627|
|Type of Material:||Conference Article|
|Journal/Proceeding Title:||5th International Workshop on Hardware and Architectural Support for Security and Privacy,|
Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.