SOUMEN ROY was born in Bagnan, Howrah, India in 1985. Presently, he has been doing research at the University of Calcutta, Kolkata, for the last 10 years on keystroke dynamics, machine learning, access control, etc. He has also been working with Bagnan College, Bagnan, Howrah, India for the last 12 years as a lecturer. He has more than a year of experience in software development. Furthermore, he has more than 30 international publications in the form of journals, edited books, and conference proceedings. He is a reviewer for various SCI/SCIE-indexed journals, including Journal of King Saud University - Computer and Information Sciences, World Wide Web Journal, Multimedia Tools and Applications, Review for Soft Computing Letters, Pattern Recognition Letters,
Efficacy of Keystroke Dynamics-based User Authentication in the Face of Language Complexity Sandip Dutta, Utpal Roy, Soumen Roy Recent Advances in Computer Science and Communications, 2025 Introduction: This study investigates the impact of language complexity on Keystroke Dynamics (KD) and its implications for accurate KD-based user authentication system performance in smartphones. Methods: This research meticulously analyzes keystroke patterns using 160 volunteers, including both frequently typed and infrequently typed texts. Our analysis of 12 anomaly detection algorithms reveals that a simple text-based KD system consistently outperforms its complex counterpart with superior Equal Error Rates (EERs). Results: As a result, the Scaled Manhattan anomaly detector achieves an EER of 2.48% for simple text and an improvement over 2.98% for complex text. The incorporation of soft biometrics further enhances algorithmic performance, emphasizing strategies to build resilience into KD-based user authentication systems. Conclusion: Throughout this study, the importance of text complexity is emphasized, and innovative pathways are introduced to strengthen KD-based user authentication paradigms.
A unique approach towards keystroke dynamics-based entry-point user access control Soumen Roy, Devadatta Sinha, Rajat Kumar Pal, Utpal Roy International Journal of Biometrics, 2024 Access control is an essential security service for computing devices, applications, and information. Among the different entry-point user access controls, keystroke dynamics (KDs) has gained popularity owing to its several merits, such as low cost, ease of usage, etc. In this study, we proposed a unique distance-based anomaly detector together with an appropriate template construction method leading to more realistic and accurate results. We validated our approach with ten standard datasets and compared the performance with 50 state-of-the-art anomaly detectors. In our consideration, recent anomaly detectors have been re-evaluated in the same experimental setting for sound comparison. An analysis of variance (ANOVA) was conducted to compare the performance of our approach to those detectors in both desktops and recent smartphones. This study provides an in-depth understanding of each detector's performance which will aid in the design of efficient KD-based access control in the next generation of smart devices and applications.
Keystroke Dynamics as a Language Profiling Tool: Identifying Mother Tongue of Unknown Internet Users Ioannis Tsimperidis, Denitsa Grunova, Soumen Roy, Lefteris Moussiades Telecom, 2023 Understanding the distinct characteristics of unidentified Internet users is helpful in various contexts, including digital forensics, targeted advertising, and user interaction with services and systems. Keystroke dynamics (KD) enables the analysis of data derived from a user’s typing behaviour on a keyboard as one approach to obtain such information. This study conducted experiments on a developed dataset that recorded samples of typing in five different mother tongues to determine Internet users’ mother tongue. Based on only a few KD features and machine learning techniques, 82% accuracy was achieved in recognising an unknown user’s mother tongue. This research highlights the potential for KD as a reliable method for identifying the mother tongue of Internet users, with implications for various applications such as improving digital forensic investigations, targeted advertising strategies, and optimising user experiences with online services.
Protection of kids from internet threats: A machine learning approach for classification of age-group based on typing pattern Lecture Notes in Engineering and Computer Science, 2018
