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Authors: Paul Houssel and Luis Leiva

Affiliation: University of Luxembourg, Luxembourg

Keyword(s): Mouse Movements, Biometrics, Authentication, Neural Networks.

Abstract: Behavioral biometrics can determine whether a user interaction has been performed by a legitimate user or an impersonator. In this regard, user re-authentication based on mouse movements has emerged as a reliable and accessible solution, without being intrusive or requiring any explicit input from the user other than regular interactions. Previous work has reported remarkably good classification performance when predicting impersonated mouse movements, however, it has relied on manual data preprocessing or ad-hoc feature extraction methods. In this paper, we design and contrast different recurrent neural networks that take as input raw mouse movements, represented by discrete sequences of coordinate derivatives (coordinate offsets relative to time), as a mean of user re-authentication that could be used on web platforms. We show that a 2-layer BiGRU model outperforms state-of-the-art approaches while being much simpler and more efficient. Our software and models are publicly available.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Houssel, P. and Leiva, L. (2024). User Re-Authentication via Mouse Movements and Recurrent Neural Networks. In Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-683-5; ISSN 2184-4356, SciTePress, pages 652-659. DOI: 10.5220/0012296600003648

@conference{icissp24,
author={Paul Houssel and Luis Leiva},
title={User Re-Authentication via Mouse Movements and Recurrent Neural Networks},
booktitle={Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP},
year={2024},
pages={652-659},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012296600003648},
isbn={978-989-758-683-5},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Information Systems Security and Privacy - ICISSP
TI - User Re-Authentication via Mouse Movements and Recurrent Neural Networks
SN - 978-989-758-683-5
IS - 2184-4356
AU - Houssel, P.
AU - Leiva, L.
PY - 2024
SP - 652
EP - 659
DO - 10.5220/0012296600003648
PB - SciTePress

- Science and Technology Publications, Lda.
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