Abstract
In the network communications, network interruption is the most vital concern these days. The expanding event of the system assaults is a staggering issue for system administrations. Different research works are now directed to locate a successful and productive answer for forestall interruption in the system so as to guarantee to arrange security and protection. Machine learning is a successful investigation device to identify any irregular occasions happened in the system traffic stream. In this paper, a mix of the decision tree and random forest algorithms is proposed to order any strange conduct in the system traffic.
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Bhavani, T.T., Rao, M.K., Reddy, A.M. (2020). Network Intrusion Detection System Using Random Forest and Decision Tree Machine Learning Techniques. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_50
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DOI: https://doi.org/10.1007/978-981-15-0029-9_50
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