An investigation of keystroke and stylometry traits for authenticating online test takers

Stewart, John; Monaco, John V.; Cha, Sung-Hyuk; Tappert, Charles C.

doi:10.1109/ijcb.2011.6117480

Cited by 43 publications

(42 citation statements)

References 19 publications

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“…Nevertheless, there has been a long history of commercially unsuccessful implementations aimed at continuous recognition of a typist. While most previous work dealt with short input (passwords or short name strings) [1,7,14,15,16], some used long free (arbitrary) text input [2,8,11,13,19,20]. Free-text input as the user continues typing allows for continuous authentication [5,12,13,17] which can be important in online exam applications [6,19].…”

Section: Introductionmentioning

confidence: 99%

Behavioral biometric verification of student identity in online course assessment and authentication of authors in literary works

Monaco

Stewart

Cha

et al. 2013

2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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Keystroke and stylometry behavioral biometrics were investigated with the objective of developing a robust system to authenticate students taking online examinations. This work responds to the 2008 U.S. Higher Education Opportunity Act that requires institutions of higher learning undertake greater access control efforts, by adopting identification technologies as they become available, to assure that students of record are those actually accessing the systems and taking the exams in online courses. Performance statistics on keystroke, stylometry, and combined keystroke-stylometry systems were obtained on data from 30 students taking examinations in a university course. The performance of the keystroke system was 99.96% and 100.00%, while that of the stylometry system was considerably weaker at 74% and 78%, on test input of 500 and 1000 words, respectively. To further investigate the stylometry system, a separate study on 30 book authors achieved performance of 88.2% and 91.5% on samples of 5000 and 10000 words, respectively, and the varied performance over the population of authors was analyzed.

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Section: Introductionmentioning

confidence: 99%

Behavioral biometric verification of student identity in online course assessment and authentication of authors in literary works

Monaco

Stewart

Cha

et al. 2013

2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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“…Stewart, et al [31] provides a comparison between keystroke dynamics and static text stylometry for verification purposes. However, Stewart and colleagues only considered stylometry on composed or fixed text.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Utilizing overt and latent linguistic structure to improve keystroke-based authentication

Goodkind

Brizan

Rosenberg

2017

Image and Vision Computing

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“…Face recognition might suffer from changing light conditions and users changing their position while working. Keystroke dynamics [5], [13] and Mouse dynamics [2], [7], [12] seem to suffer less from these natural changes in the physical environment of the user, although it is known that typing behaviour will change based on the emotional state of a person.…”

Section: Introductionmentioning

confidence: 95%

Continuous Authentication in a real world settings

Mondal¹,

Bours²

2015

2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)

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Continuous Authentication by analysing the user's behaviour profile on the computer input devices is challenging due to limited information, variability of data and the sparse nature of the information. As a result, most of the previous research was done as a periodic authentication, where the analysis was made based on a fixed number of actions or fixed time period. Also, the experimental data was obtained for most of the previous research in a very controlled condition, where the task and environment were fixed.In this paper, we will focus on actual continuous authentication that reacts on every single action performed by the user. The experimental data was collected in a complete uncontrolled condition from 52 users by using our data collection software. In our analysis, we have considered both keystroke and mouse usages behaviour pattern to avoid a situation where an attacker avoids detection by restricting to one input device because the continuous authentication system only checks the other input device. The result we have obtained from this research is satisfactory enough for further investigation on this domain.

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An investigation of keystroke and stylometry traits for authenticating online test takers

Cited by 43 publications

References 19 publications

Behavioral biometric verification of student identity in online course assessment and authentication of authors in literary works

Behavioral biometric verification of student identity in online course assessment and authentication of authors in literary works

Utilizing overt and latent linguistic structure to improve keystroke-based authentication

Continuous Authentication in a real world settings

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