Paper Info
Title
Scanning the Voice of Your Fingerprint With Everyday Surfaces
Abstract
Due to the premise of uniqueness and acceptance, fingerprint has been the most adopted biometric technologies in high-impact applications (e.g., smartphone security, monetary transactions and international-border verification). Although there are an array of commercial fingerprint scanners across different sensing modalities including optical, capacitive, thermal and ultrasonic, existing fingerprint technologies are vulnerable to spoofing attacks via fake-finger in Kang <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2003. In this paper, we investigate a new dimension of fingerprint sensing based on the friction-excited sonic wave (in simpler words, ”voice of fingerprint”) from a user swiping his fingertip on everyday surfaces. Specifically, we develop <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SonicPrint</i> to leverage the intrinsic fingerprint ridge information in sonic wave for user identification. First, the complex ambient noise is isolated from the sonic wave using background isolation and adaptive segmentation models. Afterward, a series of multi-level friction descriptors that highlight the target fingerprint information is extracted. These descriptors are fed to a specially designed ensemble classifier for user identification. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SonicPrint</i> is practical as it leverages in-built microphones in smart devices, requiring no hardware modifications. As the first exploratory study, our experimental results with 31 participants over three different swipe actions on 12 different types of materials show up to a 98 percent identification accuracy.
Year
DOI
Venue
2022
10.1109/TMC.2021.3049217
IEEE Transactions on Mobile Computing
Keywords
DocType
Volume
Adoptable biometrics,fake-finger spoofing,surface friction,fingerprint-induced sonic effect,user identification
Journal
21
Issue
ISSN
Citations 
8
1536-1233
0
PageRank 
References 
Authors
0.34
46
8
Name
Order
Citations
PageRank
Aditya Singh Rathore1295.19
Chenhan Xu200.34
Weijin Zhu300.34
Afee Daiyan400.34
Kun Wang5193.09
Feng Lin69013.94
Kui Ren77927355.27
Wenyao Xu861577.06