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Filters: Author is Kirkbride, P.  [Clear All Filters]
2021-03-18
Kirkbride, P., Dewan, M. A. Akber, Lin, F..  2020.  Game-Like Captchas for Intrusion Detection. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :312—315.

In this paper, we consider a novel method of mining biometric data for user authentication by replacing traditional captchas with game-like captchas. The game-like captchas present the user with a short game in which they attempt to get a high score. The data produced from a user's game play will be used to produce a behavior biometric based on user interactions, such as mouse movement, click patterns and game choices. The baseline expectation of interactive behavior will be used as a single factor in an intrusion detection system providing continuous authentication, considering the factors such as IP address, location, time of use, website interactions, and behavior anomalies. In addition to acting as a source of data, game-like captchas are expected to deter bots and automated systems from accessing web-based services and improving the user experience for the end-users who have become accustomed to monotonous alternatives, such as Google's re-captcha.