Behavior-Based Deepfake Detection: Leveraging Cognitive Response to Visual Face Perception

Hendrik Graupner, Hendrik Graupner, Mohammad Yeghaneh Abkenar, Mohammad Yeghaneh Abkenar, Lisa Schwetlick, Ralf Engbert, Christoph Meinel

2025

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.

Paper Citation

in Harvard Style

Graupner H., Abkenar M., 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, SciTePress, pages 964-971. DOI: 10.5220/0013256200003911

in Bibtex Style

@conference{biosignals25,
author={Hendrik Graupner and Mohammad 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},
}

in EndNote Style

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
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