Secure Human-Computer Interaction: A Multi-Factor Authentication CAPTCHA Scheme

Secure Human-Computer Interaction: A Multi-Factor Authentication CAPTCHA Scheme

Emmanuel Oluwatobi Asani (Landmark University, Nigeria), Olumide Babatope Longe (American University of Nigeria, Nigeria), Anthony Jatau Balla (Landmark University, Nigeria), Roseline Oluwaseun Ogundokun (Landmark University, Nigeria) and Emmanuel Abidemi Adeniyi (Landmark University, Nigeria)
DOI: 10.4018/978-1-7998-1279-1.ch010


In this chapter, CAPTCHA was presented as a measure for secure human-computer interaction. A multi-factor CAPTCHA scheme that integrates facial recognition and real-time functionality as a secure verification mechanism to check the activities of bots that try to assume human status was designed, developed, and tested. The real-time functionality is premised on the human user's ability to complete trivial tasks which though simple for human is difficult to break by bots. This was motivated by the need to combat attackers' tendencies to beat existing CAPTCHA schemes through optical character recognition, image annotation, tag classifier, etc. Literature on a number of existing schemes was reviewed with a view to identifying gaps and establishing the research agenda. The system design and analysis were done using scalable design techniques. Implementation was done using Javascript and a set of APIs. The scheme was tested on an intel core i7 3GHz computer and further evaluated. Preliminary results and findings show a promising effectiveness and efficiency of the developed system.
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HCI-Sec centers around the user’s need for usable and secure computers (Satchell and Dourish, 2009; González-Pérez et al., 2019). The objective is to prevent criminals or illegitimate users from gaining unauthorized access or compromising the system’s security without compromising the system’s usability. Thus, techniques for securing the systems must encompass elements of usability, because perceived difficulties often result in users resorting to practices that circumvent security or alternatively, users may seek easier to use, but insecure systems (Smith 2003; Kainda et al., 2010). Faily and Fléchais, (2010) noted that users’ biases and perception play a prominent role in the balancing of security and usability. Thus, they proposed the IRIS framework with an underlying model that integrates usability, requirements, and risk analysis. Osho et al., (2019), highlighted the increasing demand for secure systems, without compromising effectiveness engendered by usability, convenience, and cost-effectiveness.

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