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NDSS2022顶会

FakeGuard: Exploring Haptic Response to Mitigate the Vulnerability in Commercial Fingerprint Anti-Spoofing

Aditya Singh Rathore, Yijie Shen, Chenhan Xu, Jacob Snyderman, Jinsong Han, Fan Zhang, Zhengxiong Li, Feng Lin, Wenyao Xu, Kui Ren

出版方
2022年份
4顶会引用

摘要

—How to defend against presentation attacks via artificial fake fingers is a core challenge in fingerprint biometrics. The trade-off among security, usability, and production cost has driven researchers to reach a common standpoint, i.e., integrate the commercial fingerprint technology with anti-spoofing detec- tion (e.g., ridge traits). These anti-spoofing solutions are perceived as sufficiently resilient under the assumption that a fake finger can never closely relate to a live finger due to either composition of spoofing materials or non-automated manufacturing errors. In this paper, we first identify the vulnerability of in-practice antispoofing solutions in commercial fingerprint products. Instead of using expensive 3D fake fingers [1] (above USD 1000),wemimicamorerealisticscenariowhereanattackerfabricateshigh−precisionfakefingerprintsusinglow−costpolyvinylacetatematerials[2](lessthanUSD1000), we mimic a more realistic scenario where an attacker fabricates high-precision fake fingerprints using low-cost polyvinylacetate materials [2] (less than USD 50). Building on this, we introduce a practical and secure countermeasure, namely FakeGuard , to overcome the exposed vulnerability. We examine the nature of 3D haptic response effect that arises when a fingertip epidermis interacts with a tactile surface and reflects the disparate anatomy of live and fake fingers. Unlike the previous mitigation strategies, FakeGuard offers both hardware and software compatibility with existing fingerprint scanners. As the first exploration of haptic-based anti-spoofing solution, we demonstrate the capability of FakeGuard to prevent known and unknown fake finger attacks with an average detection error of 1.4%.

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