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Behavior-Based Deepfake Detection: Leveraging Cognitive Response to Visual Face Perception
Topics: Biometrics, Detection and Identification; Pattern Recognition & Machine Learning for Biosignal Data
Hendrik Graupner 1 ; 2 ; Mohammad Yeghaneh Abkenar 2 ; 3 ; Lisa Schwetlick 4 ; Ralf Engbert 5 and Christoph Meinel 1
Affiliations: 1 Hasso Plattner Institute, University of Potsdam, Potsdam, Germany ; 2 Innovations Department, Bundesdruckerei GmbH, Berlin, Germany ; 3 Department of Linguistics, University of Potsdam, Potsdam, Germany ; 4 Psychophysics Lab, Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland ; 5 Department of Psychology, University of Potsdam, Potsdam, Germany
Keyword(s): Internet Security, Deepfake Detection, Biometrics, Eye Tracking.
Abstract: Face presentation attacks are a propagating issue in an increasingly digitally interconnected world. One of the most recent developments is deepfake impersonation attacks in live video streams. Behavioral biometric analysis is a crucial part of a comprehensive solution to this pressing issue. This paper proposes the application of biological responses to visual self-recognition as a dynamic biometric trait. Self-recognition is a cognitive process that can be leveraged as in-brain identity validation. A sophisticated pre-trained model classifies eye-tracking data to determine the face in the user’s current visual focus. One eminent use case is the protection of online video conferences. This paper provides the architecture of a prototypical implementation based on an open-source video conferencing platform. Our work of interdisciplinary research aims to contribute to a holistic solution to protect our modern communication systems and restore trust in digitization.
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Paper citation in several formats:
Graupner, H., Abkenar, M. Y., Schwetlick, L., Engbert, R. and Meinel, C. (2025). Behavior-Based Deepfake Detection: Leveraging Cognitive Response to Visual Face Perception. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3; ISSN 2184-4305, SciTePress, pages 964-971. DOI: 10.5220/0013256200003911
@conference{biosignals25,
author={Hendrik Graupner and Mohammad Yeghaneh Abkenar and Lisa Schwetlick and Ralf Engbert and Christoph Meinel},
title={Behavior-Based Deepfake Detection: Leveraging Cognitive Response to Visual Face Perception},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={964-971},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013256200003911},
isbn={978-989-758-731-3},
issn={2184-4305},
}
TY - CONF
JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Behavior-Based Deepfake Detection: Leveraging Cognitive Response to Visual Face Perception
SN - 978-989-758-731-3
IS - 2184-4305
AU - Graupner, H.
AU - Abkenar, M.
AU - Schwetlick, L.
AU - Engbert, R.
AU - Meinel, C.
PY - 2025
SP - 964
EP - 971
DO - 10.5220/0013256200003911
PB - SciTePress