Biometric Presentation Attack Detection in Mobile Devices
A special issue of Digital (ISSN 2673-6470).
Deadline for manuscript submissions: closed (1 May 2021) | Viewed by 1159
Special Issue Editors
Interests: pattern recognition; machine learning; image processing; computer vision; biometrics
Interests: pattern recognition; computer vision; biometrics; digital forensics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
Biometric authentication mechanisms in mobile phone applications come with vulnerabilities to presentation attacks (PAs), challenging the effectiveness of this technology. PAs refer to techniques that inhibit the intended operation of a biometric capture system, interfering with the acquisition of the true identity. An impersonation attack can occur when a malicious individual tries to unlock the phone of someone else, for example, by presenting a printed facial image of the genuine user or a photo of his/her finger displayed using an iPad. Biometric spoofs can be detected through accurate and robust presentation attack detection (PAD) algorithms. PAD modules classify biometric samples as either live (non-spoof) or fake (spoof). The specificity of the sensor in determining a live biometric—as opposed to a recording, picture, or another non-living spoof—is commonly known as liveness detection. The latest development is therefore a subset of the potential attacks that might be detected through PAD. Despite the significant attention given to the problem of face spoofing and fingerprint recognition, PAD systems still produce poor results, through either false alarms or poor usability, lacking generalized presentation attack detection (PAD) methods performing robustly in a practical environment.
Dr. Emanuela Marasco
Dr. Gian Luca Marcialis
Dr. Maria De Marsico
Guest Editors
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Keywords
- Biometrics
- Spoofing
- Impersonation
- Mobile phones
- Security
- Presentation attacks
- Presentation attack detection algorithms
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