Iterative Keystroke Continuous Authentication: A Time Series Based Approach

Abstract

Keyboard typing patterns are a form of behavioural biometric that can be usefully employed for the purpose of user authentication. The technique has been extensively investigated with respect to the typing of fixed texts such as passwords and pin numbers, so-called static authentication. The typical approach is to compare a current "typing sample" with a typing template expressed in terms of a feature vector comprised of keystroke dynamics. The feature vector approach has also been applied in the context of continuous authentication where features are extracted from free typing. However, the use of feature vectors for keystroke continuous authentication entails a number of disadvantages, mostly associated with the size of the feature vectors and their generation, which need to capture a large number of features to be effective; thus making the technique unsuitable for iterative (real-time) authentication as would be required in the case of, for example, online assessments. To address this issue, a mechanism whereby iterative real-time keystroke continuous authentication can be achieved is proposed, by considering typing behaviour as a form of time series, that avoids the disadvantages associated with the feature vector approach. The reported experimental results show a significantly improved performance using the proposed method in comparison with the feature vector based technique.

JBCA: Designing an Adaptative Continuous Authentication Architecture

“…However, other features easier to collect, are more difficult to evaluate. The most used algorithm for processing time-based metrics is SVM [3], as these kinds of metrics often fit well in regression models. For approaches related to tracking the user's behavior (i.e.…”

TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings

“…In this work, we refer to this time as hold time. Hold time has been used in Janakiraman and Sim (2007); Sim and Janakiraman (2007); Monrose and Rubin (1997); Stewart et al (2011);Ferreira and Santos (2012); Bours (2012); Monaco et al (2013); Deutschmann et al (2013); Ahmed and Traore (2013); Çeker and Upadhyaya (2016); Mondal and Bours (2017); Alshehri et al (2017); Alshehri et al (2018); Xiaofeng et al (2019). Latency time is the time from the previous key released to the current key pressed, which has been used in Monrose and Rubin (1997); Stewart et al (2011);Rahman et al (2011); Ferreira and Santos (2012); Bours (2012); Monaco et al (2013); Ahmed and Traore (2013); Mondal and Bours (2017); Xiaofeng et al (2019).…”

“…Free text keystroke dynamics is proper for continuous user authentication because it is non-invasive, relatively cheap to realize, no additional hardware requirement, and available after the login stage (Dowland and Furnell 2004). Considerable progress has been made in free text Keystroke-based Continuous user Authentication (KCA) (Monrose and Rubin 1997;Dowland and Furnell 2004;Gunetti and Picardi 2005;Janakiraman and Sim 2007;Sim and Janakiraman 2007;Montalvão Filho and Freire 2006;Davoudi and Kabir 2009;Harun et al 2010;Stewart et al 2011;Al Solami et al 2011;Messerman et al 2011;Rahman et al 2011;Ferreira and Santos 2012;Bours 2012;Monaco et al 2013;Deutschmann et al 2013;Ahmed and Traore 2013;Kang and Cho 2015;Çeker and Upadhyaya 2016;Mondal and Bours 2017;Huang et al 2017;Ayotte et al 2019;Alshehri et al 2017;2018;Xiaofeng et al 2019). The process of a KCA algorithm is usually to collect a user's keystrokes and time stamps, extract features, and use statistical or machine learning methods to determine whether the current user is legitimate.…”

“…The process of a KCA algorithm is usually to collect a user's keystrokes and time stamps, extract features, and use statistical or machine learning methods to determine whether the current user is legitimate. Notable performances have been achieved with long (Gunetti and Picardi 2005;Çeker and Upadhyaya 2016) or short text (Alshehri et al 2017;2018;Xiaofeng et al 2019) collected by doing tasks (i.e., answering questions or transcriptions) and long data (Huang et al 2017;Ayotte et al 2019) collected in uncontrolled settings.…”

HOrBAC Optimization Based on Suspicious Behavior Detection Using Information Theory

“…An approach based on time series have been proposed for iterative continuous authentication [4]. The idea is to use sequences of keystroke dynamics in the form of time series and to monitor such time series, as a continuous data stream, by periodically extracting sub-sequences from these time series and authenticating the sub-sequences.…”