Machine Learning for Cyber Security: Mitigating Cyber Attacks and Detecting Malicious Activities in Network Traffic

ABENEZER DESALGN DANA

Diplomová práce

Abstract:

References: Dawson, M., Bacius, R., Gouveia, L. and Vassilakos, A. (2021). Understanding the Challenge of Cybersecurity in Critical Infrastructure Sectors. Land Forces Academy Review, 26(1), pp.69-75. Ferriyan, A., Thamrin, A., Takeda, K. and Murai, J. (2021). Generating Network Intrusion Detection Dataset Based on Real and Encrypted Synthetic Attack Traffic. Applied Sciences, 11(17), p.7868. Hastie, T., Tibshirani, R. and Friedman, J.H. (2017). The elements of Statistical Learning: Data Mining, Inference, and prediction. New York, NY, USA: Springer. Chow, K.H., Deshpande, U., Seshadri, S. and Liu, L. (2021). SRA: Smart Recovery Advisor for Cyber Attacks. In Proceedings of the 2021 International Conference on Management of Data (pp. 2691-2695). Kuhn, M. and Johnson, K. (2019). Applied predictive modeling. New York: Springer.

Keywords

WEKA, Machine Learning, Cyber Security, IDS

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 3. 4. 2023

Obhajoba závěrečné práce

• Obhajoba proběhla 24. 5. 2023
• Vedoucí: Ing. Tomáš Hlavsa, Ph.D.
• Oponent: Michal Kadlec, externi

Česká zemědělská univerzita v Praze

Provozně ekonomická fakulta

Magisterský studijní program / obor:
Systems Engineering and Informatics / Informatics