Affiliation:
1. Department of Electrical Engineering and Computer Science, York University, Toronto, ON M3J 1P3, Canada
Abstract
Session-replay bots are believed to be the latest and most sophisticated generation of web bots, and they are also very difficult to defend against. Combating session-replay bots is particularly challenging in online domains that are repeatedly visited by the same genuine human user(s) in the same or similar ways—such as news, banking or gaming sites. In such domains, it is difficult to determine whether two look-alike sessions are produced by the same human user or if these sessions are just bot-generated session replays. Unfortunately, to date, only a handful of research studies have looked at the problem of session-replay bots, with many related questions still waiting to be addressed. The main contributions of this paper are two-fold: (1) We introduce and provide to the public a novel real-world mouse dynamics dataset named ReMouse. The ReMouse dataset is collected in a guided environment, and, unlike other publicly available mouse dynamics datasets, it contains repeat sessions generated by the same human user(s). As such, the ReMouse dataset is the first of its kind and is of particular relevance for studies on the development of effective defenses against session-replay bots. (2) Our own analysis of ReMouse dataset using statistical and advanced ML-based methods (including deep and unsupervised neural learning) shows that two different human users cannot generate the same or similar-looking sessions when performing the same or a similar online task; furthermore, even the (repeat) sessions generated by the same human user are sufficiently distinguishable from one another.
Reference56 articles.
1. Maureen (2023, February 25). What Is Behavioral Biometric Authentication? 1Kosmos. Available online: https://www.1kosmos.com/biometric-authentication/what-is-behavioral-biometrics-authentication/.
2. A Broad Review on Non-Intrusive Active User Authentication in Biometrics;Thomas;J. Ambient. Intell. Human Comput.,2023
3. Leiva, L.A., Arapakis, I., and Iordanou, C. (2021, January 14–19). My Mouse, My Rules: Privacy Issues of Behavioral User Profiling via Mouse Tracking. Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, 51–61. CHIIR ‘21, Canberra, ACT, Australia.
4. Web-based Biometric Computer Mouse Advisory System to Analyze a User’s Emotions and Work Productivity;Kaklauskas;Biometric and Intelligent Decision Making Support,2014
5. Mouse behavioral patterns and keystroke dynamics in End-User Development: What can they tell us about users’ behavioral attributes?;Katerina;Comput. Hum. Behav.,2018
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