Abstract / truncated to 115 words (read the full abstract)

Biometric face authentication leverages the unique biological features of an individual’s face, providing a secure and convenient alternative to traditional password-based authentication. With the widespread adoption of face verification in remote authentication services and portable devices, ensuring the robustness of these systems against spoofing attacks has become increasingly critical. While traditional biometric threat models primarily focus on vulnerabilities within verification pipelines, the rise of AI-generated deepfake technology introduces a new and sophisticated attack vector. Deepfakes enable real-time manipulation of facial images, posing a significant challenge to authentication security by spoofing verification systems. This thesis addresses multiple aspects of face authentication, including face verification and attacks such as deepfake and injection attacks. It contributes to improving ... toggle 4 keywords

deepfake detection – quality assessment – face verification – injection detection

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