AI for Cybersecurity: ML-Based Techniques for Intrusion Detection Systems

Author:

Gumusbas Dilara,Yildirim Tulay

Publisher

Springer International Publishing

Reference118 articles.

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2. M.-K. Yoon, S. Mohan, J. Choi, M. Christodorescu, L. Sha, Learning execution contexts from system call distribution for anomaly detection in smart embedded system, in Proceedings of IoTDI (2017), pp. 191–196

3. G.R. Kumar, N. Mangathayaru, G. Narsimha, A novel similarity measure for intrusion detection using gaussian function. CoRR abs/1604.07510 (2016)

4. A.M. Chandrasekhar, K. Raghuveer, Intrusion detection technique by using k-means, fuzzy neural network and SVM classifiers, in 2013 International Conference on Computer Communication and Informatics, Jan 2013, pp. 1–7

5. K. Faraoun, Neural networks learning improvement using the k-means clustering algorithm to detect network intrusions. INFOCOMP J. Comput. Sci. 5, 28–36 (2006). ISSN: 1807-4545

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