Behavior Intrusion Detection System Using SVM and CNN

Author:

Chebbi Imen,Ben Younes Ahlem,Ben Ayed Leila

Publisher

Springer Nature Singapore

Reference14 articles.

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2. Fernandes, G., Rodrigues, J.J.P.C., Carvalho, L.F.: A comprehensive survey on network anomaly detection. Telecommun. Syst. 70, 447–489 (2019)

3. Guezzaz, A., Asimi, A., Tbatou, Z., Asimi, Y., Sadqi, Y.: A global intrusion detection system using PcapSockS sniffer and multilayer perceptron classifier. Int. J. Netw. Secur. 21(3), 438–450 (2019)

4. Khraisat, A., Gondal, I., Vamplew, P., Kamruzzaman, J.: Survey of intrusion detection systems: techniques, datasets and challenges. Cybersecurity, vol. 2 (2019)

5. Guezzaz, A., Asimi, Y., Azrour, M., Asimi, A.: Mathematical validation of proposed machine learning classifier for heterogeneous traffic and anomaly detection. Big Data Min. Anal. 4(1), 18–24 (2021)

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