Supervised Machine Learning Classification Algorithmic Approach for Finding Anomaly Type of Intrusion Detection in Wireless Sensor Network
Author:
Publisher
Allerton Press
Subject
Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials
Link
https://link.springer.com/content/pdf/10.3103/S1060992X20030029.pdf
Reference30 articles.
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3. Hussein, S.M., Performance evaluation of intrusion detection system using anomaly and signature based algorithms to reduction false alarm rate and detect unknown, Proc. 2016 Int. Conf. on Computational Science and Computational Intelligence (CSCI), Piscataway, NJ: Inst. Electr. Electron. Eng., 2016, pp. 1064–1069.
4. Belavagi, M.C. and Muniyal, B., Performance evaluation of supervised machine learning algorithms for intrusion detection, Procedia Comput. Sci., 2016, vol. 89, pp. 117–123.
5. Xu, C., Shen, J., Du, X., and Zhang, F., An intrusion detection system using a deep neural network with gated recurrent units, IEEE Access, 2018, vol. 6, pp. 48697–48707.
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