| Title | Investigating the Discriminative Power of Keystroke Sound |
| Publication Type | Journal Article |
| Year of Publication | 2015 |
| Authors | Roth, J., Liu, X., Ross, A., Metaxas, D. |
| Journal | IEEE Transactions on Information Forensics and Security |
| Volume | 10 |
| Pagination | 333–345 |
| ISSN | 1556-6013 |
| Keywords | Acoustic signal processing, Acoustics, authentication, authentication decision, authorisation, Continuous Authentication, continuous user authentication application, digraph latency, directed graphs, discriminative power, feature extraction, free text-based authentications, Histograms, keyboard typing, Keyboards, keystroke dynamics, keystroke dynamics modeling, Keystroke sound, keystroke sound segments, Presses, pubcrawl170115, score matching, sound streams, static text-based authentications, statistical analysis, statistical features, text analysis, Training, user recognition, virtual alphabet learning, virtual letters |
| Abstract | The goal of this paper is to determine whether keystroke sound can be used to recognize a user. In this regard, we analyze the discriminative power of keystroke sound in the context of a continuous user authentication application. Motivated by the concept of digraphs used in modeling keystroke dynamics, a virtual alphabet is first learned from keystroke sound segments. Next, the digraph latency within the pairs of virtual letters, along with other statistical features, is used to generate match scores. The resultant scores are indicative of the similarities between two sound streams, and are fused to make a final authentication decision. Experiments on both static text-based and free text-based authentications on a database of 50 subjects demonstrate the potential as well as the limitations of keystroke sound. |
| DOI | 10.1109/TIFS.2014.2374424 |
| Citation Key | roth_investigating_2015 |
Investigating the Discriminative Power of Keystroke Sound