TY - GEN
T1 - FakeGuard
T2 - 29th Annual Network and Distributed System Security Symposium, NDSS 2022
AU - Rathore, Aditya Singh
AU - Shen, Yijie
AU - Xu, Chenhan
AU - Snyderman, Jacob
AU - Han, Jinsong
AU - Zhang, Fan
AU - Li, Zhengxiong
AU - Lin, Feng
AU - Xu, Wenyao
AU - Ren, Kui
N1 - Publisher Copyright:
© 2022 29th Annual Network and Distributed System Security Symposium, NDSS 2022. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - 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 detection (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), 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%. We also examine and prove FakeGuard resilience against seven different physical attacks, e.g., brute-force through pressure variations or partial fingerprints, haptic response alteration via advanced spoofing materials or side-channel interference, and denial-of-service attacks by manipulating the moisture, lighting, and temperature of the ambient environment.
AB - 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 detection (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), 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%. We also examine and prove FakeGuard resilience against seven different physical attacks, e.g., brute-force through pressure variations or partial fingerprints, haptic response alteration via advanced spoofing materials or side-channel interference, and denial-of-service attacks by manipulating the moisture, lighting, and temperature of the ambient environment.
UR - https://www.scopus.com/pages/publications/85179847487
U2 - 10.14722/ndss.2022.24082
DO - 10.14722/ndss.2022.24082
M3 - Conference contribution
AN - SCOPUS:85179847487
T3 - 29th Annual Network and Distributed System Security Symposium, NDSS 2022
BT - 29th Annual Network and Distributed System Security Symposium, NDSS 2022
PB - The Internet Society
Y2 - 24 April 2022 through 28 April 2022
ER -