PCR-Auth: Solving Authentication Puzzle Challenge with Encoded Palm Contact Response
Long Huang, Chen Wang
Abstract
Biometrics have been widely applied as personally identifiable data for user authentication. However, existing biometric authentications are vulnerable to biometric spoofing. One reason is that they are easily observable and vulnerable to physical forgeries. Examples are the apparent surface patterns of human bodies, such as fingerprints and faces. A more significant issue is that existing authentication methods are entirely built upon biometric features, which almost never change and could be obtained or learned by an adversary such as human voices. To address this inherent security issue of biometric authentications, we propose a novel acoustically extracted hand-grip biometric, which is associated with every user’s hand geometry, body-fat ratio, and gripping strength; It is implicit and available whenever they grip a handheld device. Furthermore, we integrate a coding technique in the biometric acquisition process, which encodes static biometrics into dynamic biometric features to prevent data reuse. Additionally, this low-cost method can be deployed on any handheld device that has a speaker and a microphone. In particular, we develop a challenge-response biometric authentication system, which consists of a pair of biometric encoder and decoder. We encode the ultrasonic signal according to a challenge sequence and extract a distinct biometric code as the response for each session. We then decode the biometric code to verify the user by a convolutional neural network-based algorithm, which not only examines the coding correctness but also verifies the biometric features presented by each biometric digit. Furthermore, we investigate diverse acoustic attacks to our system, by respectively assuming an adversary could present the correct code, generate similar biometric features or successfully forge both. Extensive experiments on mobile devices show that our system achieves 97% accuracy to distinguish users and rejects 100% replay and synthesis attacks with 6-digit codes.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 8af8686d-da89-4285-a626-6fe404b36b00Cited by top-tier papers2
- "Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security ConferencesDaniel Olszewski, Allison Lu, Carson Stillman, Kevin Warren et al.CCS 2023 · 19 citations
- Low-effort VR Headset User Authentication Using Head-reverberated Sounds with Replay ResistanceRuxin Wang, Long Huang, Chen WangS&P 2023
Builds on5
- Hearing Your Voice is Not Enough: An Articulatory Gesture Based Liveness Detection for Voice AuthenticationLinghan Zhang, Sheng Tan, Jie YangCCS 2017 · 212 citations
- VoiceLive: A Phoneme Localization based Liveness Detection for Voice Authentication on SmartphonesLinghan Zhang, Sheng Tan, Jie Yang, Yingying ChenCCS 2016 · 187 citations
- VibWrite: Towards Finger-input Authentication on Ubiquitous Surfaces via Physical VibrationJian Liu, Chen Wang, Yingying Chen, Nitesh SaxenaCCS 2017 · 93 citations
- Using Reflexive Eye Movements for Fast Challenge-Response AuthenticationIvo Sluganovic, Marc Roeschlin, Kasper Bonne Rasmussen, Ivan MartinovicCCS 2016 · 93 citations
- Velody: Nonlinear Vibration Challenge-Response for Resilient User AuthenticationJingjie Li, Kassem Fawaz, Younghyun KimCCS 2019 · 55 citations
Related papers
- Voice In Ear: Spoofing-Resistant and Passphrase-Independent Body Sound AuthenticationYang Gao, Yincheng Jin, Jagmohan Chauhan, Seokmin Choi et al.UbiComp 2021 · 45 citations
- HandID: Towards Unobtrusive Gesture-independent User Authentication on Smartphones Using Vibration-based Hand BiometricsYuezhong Wu, Wei Song, Chun Tung Chou, Jiankun Hu et al.UbiComp 2025 · 1 citation
- Notification privacy protection via unobtrusive gripping hand verification using media soundsLong Huang, Chen WangMobiCom 2021 · 17 citations
- TeethPass: Dental Occlusion-based User Authentication via In-ear Acoustic SensingYadong Xie, Fan Li, Yue Wu, Huijie Chen et al.INFOCOM 2022 · 48 citations
- ChestLive: Fortifying Voice-based Authentication with Chest Motion Biometric on Smart DevicesYanjiao Chen, Meng Xue, Jian Zhang, Qianyun Guan et al.UbiComp 2022 · 20 citations
