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Detection of advanced web bots by combining web logs with mouse behavioural biometrics.

Iliou, C., Kostoulas, T., Tsikrika, T., Katos, V., Vrochidis, S. and Kompatsiaris, I., 2021. Detection of advanced web bots by combining web logs with mouse behavioural biometrics. Digital threats: research and practice, 2 (3), 24.

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DOI: 10.1145/3447815

Abstract

Web bots vary in sophistication based on their purpose, ranging from simple automated scripts to advanced web bots that have a browser fingerprint, support the main browser functionalities, and exhibit a humanlike behaviour. Advanced web bots are especially appealing to malicious web bot creators, due to their browserlike fingerprint and humanlike behaviour that reduce their detectability. This work proposes a web bot detection framework that comprises two detection modules: (i) a detection module that utilises web logs, and (ii) a detection module that leverages mouse movements. The framework combines the results of each module in a novel way to capture the different temporal characteristics of the web logs and the mouse movements, as well as the spatial characteristics of the mouse movements. We assess its effectiveness on web bots of two levels of evasiveness: (a) moderate web bots that have a browser fingerprint and (b) advanced web bots that have a browser fingerprint and also exhibit a humanlike behaviour. We show that combining web logs with visitors’ mouse movements is more effective and robust toward detecting advanced web bots that try to evade detection, as opposed to using only one of those approaches.

Item Type:Article
ISSN:2576-5337
Uncontrolled Keywords:Web bot detection, evasive web bots, advanced web bots, mouse movements, mouse biometrics, humanlike behaviour
Group:Faculty of Science & Technology
ID Code:36055
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:27 Sep 2021 10:49
Last Modified:27 Sep 2021 10:49

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