PrintListener: Uncovering the Vulnerability of Fingerprint Authentication via the Finger Friction Sound
<|reference_start|>PrintListener: Uncovering the Vulnerability of Fingerprint Authentication via the Finger Friction Sound: 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.<|reference_end|>
@article{zhou2024printlistener:,
    title={PrintListener: Uncovering the Vulnerability of Fingerprint
  Authentication via the Finger Friction Sound},
    author={Man Zhou, Shuao Su, Qian Wang, Qi Li, Yuting Zhou, Xiaojing Ma,
  Zhengxiong Li},
    journal={arXiv preprint arXiv:2404.09214},
    year={2024},
    doi={10.14722/ndss.2024.24618},
    archivePrefix={arXiv},
    eprint={2404.09214},
    primaryClass={cs.CR}
}