Enhancing CAPTCHA Security Using Interactivity, Dynamism, and Mouse Movement Patterns

Enhancing CAPTCHA Security Using Interactivity, Dynamism, and Mouse Movement Patterns

Narges Roshanbin (University of Alberta, Edmonton, Canada) and James Miller (Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada)
DOI: 10.4018/IJSSOE.2016010102
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Many existing CAPTCHAs require users to identify characters in a static image and match them with their counterparts in another image. Requiring intelligent human interaction in the matching task of these CAPTCHAs will pose a second challenge, which is straightforward for human users but difficult to emulate for Bots. In this paper, the authors develop several interactive matching tasks involving dynamic elements and demonstrate their impact on CAPTCHA security and usability in a series of tests and user studies. Their tests indicate that requiring intelligent human interaction can substantially decrease the likelihood of a CAPTCHA being broken in addition to making an attack computationally expensive. The authors' results provide both a security and a usability benchmark for the development of interactive dual-challenge CAPTCHAs. Their proposed findings from users' mouse movement data analysis can be readily incorporated in several types of existing CAPTCHA to enhance their security.
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As a security mechanism against malicious programs that may use online resources, different types of CAPTCHAs have been developed. Most primary CAPTCHAs include one problem that users need to solve to show that they are human. The problem is usually a distorted image of a sequence of characters that a user needs to recognize (e.g. Von Ahn et al. 2008; Rusu et al., 2010), an image about which the user is asked questions (e.g. Ross et al., 2010; Banday & Shah, 2009), or a distorted audio clip whose contents should be detected by the user (Shirali-Shahreza et al. 2009).

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