SOUMEN ROY

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,

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Human-Computer Interaction, Computer Science Applications, Computer Science

Scopus Publications

Authenticating Smartphone Users Continuously Even if the Smartphone is in the User’s Pocket
Sandip Dutta, Soumen Roy, and Utpal Roy
Springer Nature Switzerland



A unique approach towards keystroke dynamics-based entry-point user access control
Soumen Roy, Devadatta Sinha, Rajat Kumar Pal, and Utpal Roy
Inderscience Publishers



Keystroke Dynamics as a Language Profiling Tool: Identifying Mother Tongue of Unknown Internet Users
Ioannis Tsimperidis, Denitsa Grunova, Soumen Roy, and Lefteris Moussiades
MDPI AG
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.


Imbalanced ensemble learning in determining Parkinson's disease using Keystroke dynamics
Soumen Roy, Utpal Roy, Devadatta Sinha, and Rajat Kumar Pal
Elsevier BV



Predicting Useful Information From Typing Patterns Using a Bootstrapped-Based Homogeneous Ensemble Approach
Soumen Roy, Utpal Roy, Devadatta Sinha, and Rajat Kumar Pal
Springer Nature Singapore



A Systematic Literature Review on Latest Keystroke Dynamics Based Models
Soumen Roy, Jitesh Pradhan, Abhinav Kumar, Dibya Ranjan Das Adhikary, Utpal Roy, Devadatta Sinha, and Rajat Kumar Pal
Institute of Electrical and Electronics Engineers (IEEE)



AI for Stress Diagnosis at Home Environment
Soumen Roy, Utpal Roy, Devadatta Sinha, and Rajat Kumar Pal
Springer Nature Singapore



Identifying age group and gender based on activities on touchscreen
Soumen Roy, Devadatta Sinha, and Utpal Roy
Inderscience Publishers



Gait Identity Verification Using Equipped Smartphone Sensors
Debjyoti Ghosh, Soumen Roy, Utpal Roy, and D. D. Sinha
IEEE
A strong and convenient identity verification method is always demanded. Nowadays, the advanced sensing features like gyroscope, accelerometer and rotation information are easily available through a smartphone. These prominent and hidden features (orientation and force) created simultaneously against any activities on a smartphone that can be used in user identity verification instead of considering morphological features (video and image). Two similarity measure algorithms (Euclidean and Manhattan) have been used on the collected dataset from 63 users in 5 sessions with 4 repetitions and we got 8.7% of EER (Equal Error Rate). This study also explains the data collection tools, data capture procedure and anomaly detection for further development in this topic area.


Deep Learning Approach in Predicting Personal Traits Based on the Way User Type on Touchscreen
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer Singapore



The probability of predicting personality traits by the way user types on touch screen
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer Science and Business Media LLC



Analysis of typing pattern in identifying soft biometric information and its impact in user recognition
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer Singapore



Identifying Soft Biometric Traits Through Typing Pattern on Touchscreen Phone
Soumen Roy, Utpal Roy, and Devadatta Sinha
Springer Singapore



Protection of kids from internet threats: A machine learning approach for classification of age-group based on typing pattern




Internet of nano-things forensics: Performing digital forensics in nanoscale systems
B. Tripathy and J. Anuradha
CRC Press



Efficacy of Typing Pattern Analysis in Identifying Soft Biometric Information and Its Impact in User Recognition
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer International Publishing



Security Enhancement of Knowledge-based User Authentication through Keystroke Dynamics
Soumen Roy, Utpal Roy, and D. D. Sinha
EDP Sciences
Keystroke Dynamics is a behavioural biometrics characteristic in Biometric science, which solve the issues in user identification or verification. In Knowledge-based user authentication technique, we compromise with PIN or password which is unsafe due to different type of attacks. It is good to choose password with the combination of upper and lower case letter with some digits and symbols, but which is very hard to remember or generally we forget to distinguish those passwords for different access control systems. Our system not only takes the users’ entered texts but their typing style is also account for. In our experiment, we have not taken hard password type texts, we have chosen some daily used words where users are habituated and comfortable at typing and we obtained the consisting typing pattern. Different distance-based and data mining algorithms we have applied on collected typing pattern and obtained impressive results. As per our experiment, if we use keystroke dynamics in existing knowledge based user authentication system with minimum of five daily used common texts then it increases the security level up to 97.6% to 98.2% (if we remove some of the irrelevant feature sets).


Comparative study of various features-mining-based classifiers in different keystroke dynamics datasets
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer International Publishing



Free-text user authentication technique through keystroke dynamics
Soumen Roy, Utpal Roy, and D. D. Sinha
IEEE
Some common words (name, address, E-mail ID, ...), we press daily and we are habituated to press it in same rhythm, which is unique and can be used to segregate and distinguish people. In this paper we are considering rhythm not only the entered common words or some sequence of common characters. Here machine intelligence relies on the fact that it stores the typing style of some daily used words which are supported by the user and can be used as a secret key. Recognising typing style promises a parameter like behavioural biometric characteristics that may facilitate non-intrusive, cost-effective and continuous monitoring. But this technique, as of now, suffers from accuracy level and performance. In order to realize, this technique in practice a higher level of security and performance together with low cost version is needed with an error to an accepted level. Hence, it is highly essential to identify the controlling parameters and optimise the accuracy and performance as well as cost with new algorithms.


Password recovery mechanism based on keystroke dynamics
Soumen Roy, Utpal Roy, and D. D. Sinha
Springer India

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