Robust Keystroke Behavior Features for Continuous User Authentication for Online Fraud Detection
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3243-6_71
Reference19 articles.
1. Kochegurova EA, Martynova YA (2020) Aspects of continuous user identification based on free texts and hidden monitoring. Program Comput Softw 46(1):12–24. https://doi.org/10.1134/S036176882001003X
2. Andrean A, Jayabalan M, Thiruchelvam V (2020) Keystroke dynamics based user authentication using deep multilayer perceptron. Int J Mach Learn Comput 10(1):134–139
3. Jain AK, Ross A, Pankanti S (2006) Biometrics: a tool for information security. IEEE Trans Inf Forensics Secur 1(2):125–143. https://doi.org/10.1109/TIFS.2006.873653
4. Subash A, Song I (2021) Real-time behavioral biometric information security system for assessment fraud detection. In: 2021 IEEE international conference on computing (ICOCO), pp 186–191. https://doi.org/10.1109/ICOCO53166.2021.9673568
5. Sadikan SFN, Ramli AA, Fudzee MFM (2019) A survey paper on keystroke dynamics authentication for current applications. AIP Conf Proc 2173(1). https://doi.org/10.1063/1.5133925
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