期刊
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
卷 15, 期 -, 页码 1572-1585出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIFS.2019.2944058
关键词
Lips; Authentication; Smart phones; Biometrics (access control); Acoustics; Sensors; Microphones; Authentication; multimodal biometrics; acoustic sensing
资金
- NSFC [61822207, U1636219]
- Equipment Pre-Research Joint Fund of Ministry of Education of China (Youth Talent) [6141A02033327]
- Outstanding Youth Foundation of Hubei Province [2017CFA047]
- National Natural Science Foundation of China [61972296, 61702380, 61772377, 61572370]
- Wuhan Advanced Application Project [2019010701011419]
- Hubei Provincial Technological Innovation Special Funding Major Projects [2017AAA125]
- Natural Science Foundation of Hubei Province of China [2017CFA007]
- Science and Technology Planning Project of Shenzhen [JCYJ20170818112550194]
Voice authentication is becoming increasingly popular, which offers potential benefits over knowledge and possession based authentication methods. Meanwhile, the unique features of lip movements during speaking have been proved to be useful for authentication. However, the unimodal biometric authentication systems based on either voice or lip movements have certain limitations. Voice authentication systems are prone to spoofing attacks and suffer from serious performance degradation in noisy environments. Lip movements authentication systems are unstable and are sensitive to the user's physical and psychological conditions. In this paper, we propose and implement LVID, a multimodal biometrics authentication system on smartphones, which resolves the defects of the original systems by combining the advantages of lip movements and voice. LVID simultaneously captures these two biometrics with the built-in audio devices on smartphones and fuses them at the data level. The reliable and effective features are then extracted from the fused data for authentication. LVID is practical as it requires neither cumbersome operations nor additional hardwares but only a speaker and a microphone that are commonly available on smartphones. Our experimental results with 104 participants show that LVID can achieve 95 accuracy for user authentication, and 93.47 of the attacks can be detected. It is also verified that LVID works well with different smartphones and is robust to different smartphone positions.
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