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Original Article
Machine Learning Approaches for User Authentication Anomaly Detection
Sneh Lata Singh1
Mohd. Suhail2
Prashant Kandpal3
Prashant Upreti4
Priyanshu Verma5
Saksham Chauhan6
1 Assistant professor, Department of Computer Science and Engineering, Dr. A.P.J Abdul Kalam Institute of Technology, Tanakpur Champawat, India. 2 3 4 5 6 Department of Artificial Intelligence and Machine Learning, Dr. A.P.J Abdul Kalam Institute of Technology, Tanakpur Champawat, India.
Published Online: September-December 2025
Pages: 292-300
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250403046References
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cybersecurity data streams," in Proc. AAAI Workshop Artif. Intell. Cyber Security, 2017, pp. 224-231.
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Proc. IEEE Int. Conf. Cyber Security Cloud Comput., 2017, pp. 302-307.
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Symp., 2018.
7. L. Breiman, "Random forests," Mach. Learn., vol. 45, no. 1, pp. 5-32, 2001.
2. T. Tuor, S. Kaplan, B. Hutchinson, N. Nichols, and S. Robinson, "Deep learning for unsupervised insider threat detection in structured
cybersecurity data streams," in Proc. AAAI Workshop Artif. Intell. Cyber Security, 2017, pp. 224-231.
3. R. Zuech, T. M. Khoshgoftaar, and R. Wald, "Intrusion detection and big heterogeneous data: A survey," J. Big Data, vol. 2, no. 1, pp. 1-41,
2015.
4. M. Gharib, P. Lollini, A. Ceccarelli, and A. Bondavalli, "Engineering-based approach to quantitatively assure security of critical systems,"
IEEE Trans. Reliab., vol. 68, no. 3, pp. 1180-1194, 2019.
5. A. Sapegin, A. Amirkhanyan, M. Gawron, F. Cheng, and C. Meinel, "Unified visualization of security threats using augmented reality," in
Proc. IEEE Int. Conf. Cyber Security Cloud Comput., 2017, pp. 302-307.
6. M. Mirsky et al., "Kitsune: An ensemble of autoencoders for online network intrusion detection," in Proc. Network Distrib. Syst. Security
Symp., 2018.
7. L. Breiman, "Random forests," Mach. Learn., vol. 45, no. 1, pp. 5-32, 2001.
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