Anti-spoofing study on palm biometric features

被引:5
|
作者
Wang, Haixia [1 ]
Su, Lixun [2 ]
Zeng, Hongxiang [2 ]
Chen, Peng [1 ]
Liang, Ronghua [1 ]
Zhang, Yilong [1 ]
机构
[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Peoples R China
[2] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Peoples R China
基金
中国国家自然科学基金;
关键词
Anti-spoofing; Dynamic biometrics; SpO2; Pulse; Palm; PRESENTATION ATTACK DETECTION; OXYGEN-SATURATION; VEIN RECOGNITION; FUSION;
D O I
10.1016/j.eswa.2023.119546
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Spoofing attacks severely threaten the security of biometric recognition systems. Two concerns are raised regarding palm biometrics. First, the anti-spoofing ability of the palm vein as a subcutaneous feature needs further exploration. In-depth research is in need. Second, the capability of the palmprint and palm vein in liv-eness detection has been underestimated. Extracting extra liveness information for spoofing detection is urgently needed. This study proposes a dual-wavelength synchronous acquisition system for palm biometrics. Static biometrics of palmprint and palm vein and dynamic biometrics of SpO2 and pulse are captured and extracted. The proposed system maintains the recognition ability of the palm biometric system and achieves high anti -spoofing ability without additional hardware requirements. Under the proposed scheme, most hand feature measurement systems can be upgraded to obtain liveness information with minimal adjustment. A three-layer anti-spoofing strategy is also proposed based on the dynamic features. Based on the analysis of the human skin, various artificial palmprints and palm veins are fabricated using a variety of materials. Experiments investigated the anti-spoofing capabilities of palm biometrics. The results show that the proposed system can accurately extract SpO2 and pulse from palmprint and palm vein images, and SpO2 and pulse can significantly increase the anti-spoofing capability of palm biometrics.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] ANALYSIS OF TEXTURAL FEATURES FOR FACE BIOMETRIC ANTI-SPOOFING
    Waris, Muhammad-Adeel
    Zhang, Honglei
    Ahmad, Iftikhar
    Kiranyaz, Serkan
    Gabbouj, Moncef
    2013 PROCEEDINGS OF THE 21ST EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2013,
  • [2] GANBA: Generative Adversarial Network for Biometric Anti-Spoofing
    Gomez-Alanis, Alejandro
    Gonzalez-Lopez, Jose A.
    Peinado, Antonio M.
    APPLIED SCIENCES-BASEL, 2022, 12 (03):
  • [3] Iris Anti-spoofing Solution for Mobile Biometric Applications
    Odinokikh, Gleb
    Efimov, Yurii
    Solomatin, Ivan
    Korobkin, Mikhail
    Matveev, Ivan
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (ICPRAI 2018), 2018, : 667 - 671
  • [4] Iris Anti-Spoofing Solution for Mobile Biometric Applications
    Odinokikh G.
    Efimov I.
    Solomatin I.
    Korobkin M.
    Matveev I.
    Pattern Recognition and Image Analysis, 2018, 28 (4) : 670 - 675
  • [5] A REVIEW OF IRIS ANTI-SPOOFING
    Galbally, Javier
    Gomez-Barrero, Marta
    2016 4TH INTERNATIONAL WORKSHOP ON BIOMETRICS AND FORENSICS (IWBF), 2016,
  • [6] A Survey of GNSS Spoofing and Anti-Spoofing Technology
    Meng, Lianxiao
    Yang, Lin
    Yang, Wu
    Zhang, Long
    REMOTE SENSING, 2022, 14 (19)
  • [7] Towards face anti-spoofing
    Syed, Muhammad Ibrahim
    Asif, Amina
    Shahzad, Mohsin
    Khan, Uzair
    Khan, Sumair
    Mahmood, Zahid
    JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE, 2023,
  • [8] Anti-Spoofing Method for Iris Recognition by Combining the Optical and Textural Features of Human Eye
    Lee, Eui Chul
    Son, Sung Hoon
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2012, 6 (09): : 2424 - 2441
  • [9] Linear prediction residual features for automatic speaker verification anti-spoofing
    Hanilci, Cemal
    MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (13) : 16099 - 16111
  • [10] Linear prediction residual features for automatic speaker verification anti-spoofing
    Cemal Hanilçi
    Multimedia Tools and Applications, 2018, 77 : 16099 - 16111