TouchSignatures: Identification of User Touch Actions and PINs Based on Mobile Sensor Data via JavaScript
Maryam Mehrnezhad, Ehsan Toreini, Siamak F. Shahandashti, and Feng Hao.
Journal of Information Security and Applications, 26: 23–38, Elsevier, 2016.
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Abstract
Conforming to W3C specifications, mobile web browsers allow JavaScript code in a web page to access motion and orientation sensor data without the user's permission. The associated risks to user security and privacy are however not considered in W3C specifications. In this work, for the first time, we show how user security can be compromised using these sensor data via browser, despite that the data rate is 3 to 5 times slower than what is available in app. We examine multiple popular browsers on Android and iOS platforms and study their policies in granting permissions to JavaScript code with respect to access to motion and orientation sensor data. Based on our observations, we identify multiple vulnerabilities, and propose TouchSignatures which implements an attack where malicious JavaScript code on an attack tab listens to such sensor data measurements. Based on these streams, TouchSignatures is able to distinguish the user's touch actions (i.e., tap, scroll, hold, and zoom) and her PINs, allowing a remote website to learn the client-side user activities. We demonstrate the practicality of this attack by collecting data from real users and reporting high success rates using our proof-of-concept implementations. We also present a set of potential solutions to address the vulnerabilities. The W3C community and major mobile browser vendors including Mozilla, Google, Apple and Opera have acknowledge our work and are implementing some of our proposed countermeasures.
Industry Impact
Firefox, Apple (ID: CVE-2016-1780), Chromium, W3C Specification
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Newcastle University press release
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