University of Oulu

A. K. Belman et al., "Authentication by Mapping Keystrokes to Music: The Melody of Typing," 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), Amaravati, India, 2020, pp. 1-6, doi: 10.1109/AISP48273.2020.9073125

Authentication by mapping keystrokes to music : the melody of typing

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Author: Belman, Amith K.1; Paul, Tirthankar2; Wang, Li3;
Organizations: 1Syracuse University
2University of Oulu
3Florida International University
4Pozna University of Technology
5University at Buffalo, SUNY
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-05-11


Expressing Keystroke Dynamics (KD) in form of sound opens new avenues to apply sound analysis techniques on KD. However this mapping is not straight-forward as varied feature space, differences in magnitudes of features and human interpretability of the music bring in complexities. We present a musical interface to KD by mapping keystroke features to music features. Music elements like melody, harmony, rhythm, pitch and tempo are varied with respect to the magnitude of their corresponding keystroke features. A pitch embedding technique makes the music discernible among users. Using the data from 30 users, who typed fixed strings multiple times on a desktop, shows that these auditory signals are distinguishable between users by both standard classifiers (SVM, Random Forests and Naive Bayes) and humans alike.

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Series: Symposium on Photonics and Optoelectronics
ISSN: 2156-8464
ISSN-E: 156-8480
ISSN-L: 2156-8464
ISBN: 978-1-7281-4458-0
ISBN Print: 978-1-7281-4456-6
Pages: 1 - 6
DOI: 10.1109/AISP48273.2020.9073125
Host publication: Proceedings of the 2020 International Conference on Artificial Intelligence and Signal Processing (AISP), January 10-12, 2020, VIT-AP University, AMaravati, Andhra Pradesh, India
Conference: Artificial Intelligence and Signal Processing (AISP)
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was supported in part by the US National Science Foundation (US NSF) under Grant SaTC-1527795 and US Army Research Office under Grant W911NF-15-1-0572.
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