Zero-Day Threats Detection for Critical Infrastructures
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-39652-6_3
Reference15 articles.
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2. Kasongo, S.M.: Genetic algorithm based feature selection technique for optimal intrusion detection. Preprints (2021)
3. Nkongolo, M., Van Deventer, J.P., Kasongo, S.M.: Ugransome1819: a novel dataset for anomaly detection and zero-day threats. Information 12(10), 405 (2021)
4. Suthar, F., Patel, N., Khanna, S.: A signature-based botnet (emotet) detection mechanism. Int. J. Eng. Trends Technol. 70, 185–193 (2022)
5. Shankar, D., George, G.V.S., Janardhana Naidu, J.N.S.S., Madhuri, P.S.: Deep analysis of risks and recent trends towards network intrusion detection system. Int. J. Adv. Comput. Sci. Appl. 14(1) (2023)
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