Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 412-423 |
Journal / Publication | IEEE Transactions on Biometrics, Behavior, and Identity Science |
Volume | 4 |
Issue number | 3 |
Online published | 2 Jun 2022 |
Publication status | Published - Jul 2022 |
Externally published | Yes |
Link(s)
Abstract
This paper investigates whether computer usage profiles comprised of process-, network-, mouse-, and keystroke-related events are unique and consistent over time in a naturalistic setting, discussing challenges and opportunities of using such profiles in applications of continuous authentication. We collected ecologically-valid computer usage profiles from 31 MS Windows 10 computer users over 8 weeks and submitted this data to comprehensive machine learning analysis involving a diverse set of online and offline classifiers. We found that: (i) profiles were mostly consistent over the 8-week data collection period, with most (83.9%) repeating computer usage habits on a daily basis; (ii) computer usage profiling has the potential to uniquely characterize computer users (with a maximum F-score of 99.90%); (iii) network-related events were the most relevant features to accurately recognize profiles (95.69% of the top features distinguishing users were network-related); and (iv) binary models were the most well-suited for profile recognition, with better results achieved in the online setting compared to the offline setting (maximum F-score of 99.90% vs. 95.50%).
Research Area(s)
- Analytical models, Behavioral sciences, Biological system modeling, Biometrics (access control), Computational modeling, Computer security, Computer user profiling, continuous authentication, machine learning, time series analysis, user study
Citation Format(s)
Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles. / Giovanini, Luiz; Ceschin, Fabrício; Silva, Mirela et al.
In: IEEE Transactions on Biometrics, Behavior, and Identity Science, Vol. 4, No. 3, 07.2022, p. 412-423.
In: IEEE Transactions on Biometrics, Behavior, and Identity Science, Vol. 4, No. 3, 07.2022, p. 412-423.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review