User authentication through biometric sensors and decision fusion

Acharya, Sayandeep; Fridman, Alexander; Brennan, Patrick McKinley; Juola, Patrick; Greenstadt, Rachel; Kam, Moshe

doi:10.1109/ciss.2013.6552271

Cited by 10 publications

(7 citation statements)

References 21 publications

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“…We have found that all the state of the art experiments on continuous authentication, which combines keystroke and mouse dynamics both was done in a very controlled lab environments followed by a predefined task and also used only predefined applications [1], [4], [9], [14]. Based on our understanding these experiments are the starting point to understand the science behind the continuous authentication but, not enough to extend it to the real world situation.…”

Section: A Discussionmentioning

confidence: 95%

“…Based on our understanding these experiments are the starting point to understand the science behind the continuous authentication but, not enough to extend it to the real world situation. We would also like to test and compare our proposed scheme on another dataset used in the state of the art research [1], [4], [9], [14] but, due to unavailability of these datasets limit the comparison with previous work.…”

Section: A Discussionmentioning

confidence: 99%

“…We would also like to mention that any given time the user can only perform either mouse action or key action but not both at the same time. Therefore, we do not need any multi modality fusion architecture for our analysis that was recently seen in the previous work [1], [4], [9], [14].…”

Section: B System Architecturementioning

confidence: 96%

“…This system uses the behaviour of the user to determine the trust the system has in the genuineness of that user. In particular, it will focus on input of the user via mouse and keyboard to avoid the situation where an attacker avoids detection by restricting to one input device because the system only checks the other input device [1], [4], [9], [14]. The behaviour of the current user will be compared with the stored information of the behaviour of the genuine user and as a result of that comparison the trust of the system in the user will increase or decrease and access to the computer will be blocked if the trust in the genuineness of the user is too low.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: A Discussionmentioning

confidence: 95%

Section: A Discussionmentioning

confidence: 99%

Section: B System Architecturementioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Continuous Authentication in a real world settings

Mondal¹,

Bours²

2015

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

View full text Add to dashboard Cite

show abstract

“…This system uses the behaviour of the user to determine the trust the system has in the genuineness of that user. In particular, it will focus on input of the user via mouse and keyboard to avoid the situation where an attacker avoids detection by restricting to one input device because the system only checks the other input device [1,4,11,21]. The behaviour of the current user will be compared with the stored information of the behaviour of the genuine user and as a result of that comparison the trust of the system in the user will increase or decrease and access to the computer will be blocked if the trust in the genuineness of the user is too low.…”

Section: Introductionmentioning

confidence: 99%

Continuous Authentication using Fuzzy Logic

Mondal

Bours

2014

Proceedings of the 7th International Conference on Security of Information and Networks

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In this paper, we investigate the performance of a continuous authentication system using fuzzy logic techniques. The system monitors mouse and keystroke dynamics behaviour of a user to determine the genuineness. The objective was to design a system that is capable of detecting an impostor user as fast as possible, while not disturbing the genuine user. For our research we build a new dataset consisting of mouse and keystroke dynamics behavioural data of 52 persons, collected in a real life environment (no control over environment or performed tasks) over a period of 5-7 days.Using fuzzy logic techniques we found that the objectives were not completely met, meaning that some impostors were not detected by the system and that some genuine users were locked out by the system, but the results are satisfactory enough to serve as a good starting point for this research.

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