A Review on Intrusion Detection System using Artificial Intelligence Approach


  • Apoorva Deshpande P.G. Student, Department of Computer Science and Engineering, MPCT, Gwalior, India
  • Ramnaresh Sharma Associate Professor, Department of Computer Science and Engineering, MPCT, Gwalior, India




Today, intrusion detection system using the neural network is an interested and considerable area for the research community. The computational intelligence systems are defined on the basis of the following parameters: fault tolerance and adaptation; adaptable the requirements of make a better intrusion detection model. In this paper, provide an overview of the research progress using computational intelligence to the problem of intrusion detection. The goal of this paper summarized and compared research contributions of Intrusion detection system using computational intelligence and neural network, define existing research challenges and anticipated solution of machine learning. Research showed that application of machine learning techniques in intrusion detection could achieve high detection rate. Machine learning and classification algorithms help to design "Intrusion Detection Models" which can classify the network traffic into intrusive or normal traffic. This paper discusses some commonly used machine learning techniques in Intrusion Detection System and also reviews some of the existing machine learning IDS proposed by researchers at different times.


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How to Cite

Deshpande, A., & Sharma, R. . (2018). A Review on Intrusion Detection System using Artificial Intelligence Approach. SMART MOVES JOURNAL IJOSCIENCE, 4(8), 10–15. https://doi.org/10.24113/ijoscience.v4i8.153