PrintListener: Uncovering the Vulnerability of Fingerprint Authentication via the Finger Friction Sound
Man Zhou, Shuao Su, Qian Wang, Qi Lecky Li, Yuting Zhou, Xiaojing Ma, Zhengxiong Li · 2024
Fingerprint authentication has been extensively employed in contemporary identity verification systems owing to its rapidity and cost-effectiveness.Due to its widespread use, fingerprint leakage may cause sensitive information theft, enormous economic and personnel losses, and even a potential compromise of national security.As a fingerprint that can coincidentally match a specific proportion of the overall fingerprint population, MasterPrint rings the alarm bells for the security of fingerprint authentication.In this paper, we propose a new side-channel attack on the minutiae-based Automatic Fingerprint Identification System (AFIS), called PrintListener, which leverages users' fingertip swiping actions on the screen to extract fingerprint pattern features (the first-level features) and synthesizes a stronger targeted PatternMasterPrint with potential second-level features.The attack scenario of PrintListener is extensive and covert.It only needs to record users' fingertip friction sound and can be launched by leveraging a large number of social media platforms.Extensive experimental results in realworld scenarios show that Printlistener can significantly improve the attack potency of MasterPrint.