Intern
Chair of Computer Science II - Software Engineering

Liveness Detection for Facial Authentication Systems

09.01.2022

Facial authentication systems are being used globally to ease the authentication process of various applications.

Facial authentication systems are being used globally to ease the authentication process of various applications. Attackers have become interested in bypassing such systems in order to gain illicit access to restricted areas. Aggravatingly, past research has shown that state-of-the-art facial authentication systems are vulnerable to simple attacks. This project works on a Machine Learning based solution that detects the presence of attacks and thereby provides resilience for existing facial authentication systems.

People involvedProf. A. DmitrienkoMoritz Finke.

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