TouchSignatures: Identification of User Touch Actions and PINs Based on Mobile Sensor Data via JavaScript
Maryam Mehrnezhad, Ehsan Toreini, Siamak F. Shahandashti, Feng Hao

TL;DR
This paper reveals security vulnerabilities in mobile browsers that allow malicious JavaScript to access sensor data and identify user touch actions and PINs, posing significant privacy risks.
Contribution
It demonstrates for the first time how sensor data accessible via JavaScript can be exploited to infer user activities and PINs, and proposes countermeasures.
Findings
High success rate in identifying touch actions and PINs
Vulnerabilities exist across multiple popular browsers
Proposed solutions are being adopted by browser vendors
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,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
