Cracking Android pattern lock in five attempts

Ye, Guixin and Tang, Zhanyong and Fang, Dingyi and Chen, Xiaojiang and Kim, Kwang In and Taylor, Ben and Wang, Zheng (2017) Cracking Android pattern lock in five attempts. In: Proceedings 2017 Network and Distributed System Security Symposium 2017 (NDSS'17) :. Internet Society, Reston VA, 0-0. ISBN 1891562460

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Abstract

Pattern lock is widely used as a mechanism for authentication and authorization on Android devices. This paper presents a novel video-based attack to reconstruct Android lock patterns from video footage filmed using a mobile phone camera. Unlike prior attacks on pattern lock, our approach does not require the video to capture any content displayed on the screen. Instead, we employ a computer vision algorithm to track the fingertip movements to infer the pattern. Using the geometry information extracted from the tracked fingertip motions, our approach is able to accurately identify a small number of (often one) candidate patterns to be tested by an adversary. We thoroughly evaluated our approach using 120 unique patterns collected from 215 independent users, by applying it to reconstruct patterns from video footage filmed using smartphone cameras. Experimental results show that our approach can break over 95% of the patterns in five attempts before the device is automatically locked by the Android operating system. We discovered that, in contrast to many people’s belief, complex patterns do not offer stronger protection under our attacking scenarios. This is demonstrated by the fact that we are able to break all but one complex patterns (with a 97.5% success rate) as opposed to 60% of the simple patterns in the first attempt. Since our threat model is common in day-to-day life, this paper calls for the community to revisit the risks of using Android pattern lock to protect sensitive information.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
82868
Deposited By:
Deposited On:
06 Dec 2016 09:52
Refereed?:
Yes
Published?:
Published
Last Modified:
10 Oct 2024 00:43