df9c43a5-ea31-4b0c-a710-c85af1bbf9cc20250724124639276wseas:wseasmdt@crossref.orgMDT DepositWSEAS TRANSACTIONS ON SYSTEMS AND CONTROL2224-28561991-876310.37394/23203http://wseas.org/wseas/cms.action?id=40731720251720252010.37394/23203.2025.20https://wseas.com/journals/sac/2025.phpTanapatAnusas-AmornkulDepartment of Computer and Information Science, King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1 Road, Wongsawang, Bangsue, Bangkok 10800, THAILANDThagoonPhigoonkhaoDepartment of Computer and Information Science, King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1 Road, Wongsawang, Bangsue, Bangkok 10800, THAILANDPassword authentication is a well-known and widespread technique for user authentication. However, with highly developed technologies nowadays, password authentication has become less effective in guarding against a password-guessing attack. Therefore, two-factor authentication is used to enhance password authentication. In this work, the password and keystroke dynamics of a username are used to enhance the classical authentication scheme, which is known as two-factor authentication. Keystroke dynamics is a biometric authentication involved with individual typing behavior parameters: hold time, interkey time, and latency time. This work proposed extracting basic statistical features, which are mean and median, to create 3D trajectory curves. The 3D curve of a user is compared point-by-point with a master keystroke profile by computing using Euclidean, Manhattan, and Mahalanobis distances. The result demonstrates that a 3D trajectory dissimilarity using mean and Euclidean distance methods gives the highest efficiency using the Confusion matrix with accuracy and F1-Score of 99.07% and 0.95, respectively. In addition, a false acceptance rate (FAR), a false rejection rate (FRR), and an equal error rate (EER) for the proposed work are 0.74%, 2.66%, and 0.93%, accordingly.7182025718202529630433https://wseas.com/journals/sac/2025/a665103-029(2025).pdf10.37394/23203.2025.20.33https://wseas.com/journals/sac/2025/a665103-029(2025).pdf10.1109/kse.2016.7758068H. N. Ngoc and N. T. Nguyen, An enhanced distance metric for keystroke dynamics classification, 2016 Eighth International Conference on Knowledge and Systems Engineering (KSE), Hanoi, Vietnam, 2016, pp. 285-290, doi: 10.1109/KSE.2016.7758068. 10.1109/jcsse.2017.8025915M. I. W. Pramana, Suhardi, N. B. Kurniawan and J. Sembiring, Keystroke dynamics for authentication using dynamic time warping, in 2017 14th International Joint Conference on Computer Science and Software Engineering (JCSSE), NakhonSiThammarat, 2017, pp. 1-5, doi: 10.1109/JCSSE.2017.8025915. 10.1109/pst47121.2019.8949031A. Foresi and R. 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Khan, Keystroke recognition using neural network, 2017 5th International Symposium on Computational and Business Intelligence (ISCBI), Dubai, United Arab Emirates, 2017, pp. 86-90, doi: 10.1109/ISCBI.2017.8053550. 10.1109/cits.2019.8862068A. Daribay, M. S. Obaidat and P. V. Krishna, Analysis of Authentication System Based on Keystroke Dynamics, 2019 International Conference on Computer, Information and Telecommunication Systems (CITS), Beijing, China, 2019, pp. 1-6, doi: 10.1109/CITS.2019.8862068. 10.1109/cybersecpods.2019.8885203Y. Patel, K. Ouazzane, V. T. Vassilev, I. Faruqi and G. L. Walker, Keystroke Dynamics using Auto Encoders, 2019 International Conference on Cyber Security and Protection of Digital Services (Cyber Security), Oxford, UK, 2019, pp. 1-8, doi: 10.1109/CyberSecPODS.2019.8885203. 10.1109/iscturkey51113.2020.9307967K. Bicakci, O. Salman, Y. Uzunay and M. Tan, Analysis and Evaluation of Keystroke Dynamics as a Feature of Contextual Authentication, 2020 International Conference on Information Security and Cryptology (ISCTURKEY), Ankara, Turkey, 2020, pp. 11-17, doi: 10.1109/ISCTURKEY51113.2020.9307967. 10.1109/cw52790.2021.00056A. Mhenni, C. Rosenberger and N. E. B. Amara, Keystroke Dynamics Classification Based On LSTM and BLSTM Models, 2021 International Conference on Cyberworlds (CW), Caen, France, 2021, pp. 295-298, doi: 10.1109/CW52790.2021.00056. 10.1109/icsintesa62455.2024.10747905I. Singh, Manav, M. Gautam and M. Toshwal, Hybrid Golden Jackal-Sea Lion and Sea Horse Optimization Algorithm for Improved Keystroke Dynamics User Authentication, 2024 4th International Conference of Science and Information Technology in Smart Administration (ICSINTESA), Balikpapan, Indonesia, 2024, pp. 50-55, doi: https://doi.org/10.1109/ICSINTESA62455.20 24.10747905.