NLP-based User Authentication through Mouse Dynamics

Hoseong Lee, Nikhil Prathapani, Rajesh Paturi, Sarp Parmaksiz, Fabio Di Troia

2022

Abstract

Insider threat attacks are increasing in most organizations yearly. It is also tough to prevent this type of attack because the threat is within the boundary, making them more dangerous than external threat actors. There can be a situation where a strong authentication layer is implemented for the external users, but due to cost or maintenance effort reasons, the authentication layer for insiders might not have proper security controls. One of the types of insider threat attacks is to exploit established sessions by legitimate users. There are certain applications and operating systems that provide an in-built security mechanism to detect idle sessions and automatically expire the sessions if no action is performed by the user. However, this type of protection is still vulnerable since it cannot really detect if the user who is taking action is the legitimate user or not. In this paper, we propose to use an advanced machine learning model based on Natural Language Processing (NLP) algorithms to authenticate users based on their mouse dynamics in web browser contexts. The model can provide a protective layer that continuously monitors against insider threat attacks. By this method, we can prevent malicious users from accessing unauthorized assets and provide enhanced security to legitimate users.

Paper Citation

in Harvard Style

Lee H., Prathapani N., Paturi R., Parmaksiz S. and Di Troia F. (2022). NLP-based User Authentication through Mouse Dynamics. In Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ForSE, ISBN 978-989-758-553-1, pages 696-702. DOI: 10.5220/0011005900003120

in Bibtex Style

@conference{forse22,
author={Hoseong Lee and Nikhil Prathapani and Rajesh Paturi and Sarp Parmaksiz and Fabio Di Troia},
title={NLP-based User Authentication through Mouse Dynamics},
booktitle={Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ForSE,},
year={2022},
pages={696-702},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011005900003120},
isbn={978-989-758-553-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Information Systems Security and Privacy - Volume 1: ForSE,
TI - NLP-based User Authentication through Mouse Dynamics
SN - 978-989-758-553-1
AU - Lee H.
AU - Prathapani N.
AU - Paturi R.
AU - Parmaksiz S.
AU - Di Troia F.
PY - 2022
SP - 696
EP - 702
DO - 10.5220/0011005900003120