Computation of Risk Severity of the Malicious Node using Adaptive Neuro Fuzzy Inference System (ANFIS)

Authors

  • R. Dharmarajan Research Scholar, Department of Computer Science, Manonmaniam Sundaranar University, Tamil Nadu
  • V. Thiagarasu Associate Professor, Department of Computer Science, Gobi Arts and Science College, Erode, Tamil Nadu

DOI:

https://doi.org/10.51983/ajeat-2019.8.1.1067

Keywords:

Wireless Network, Fuzzy Logic, Adaptive Neuro Fuzzy Inference System, Membership Function, KDDCUP dataset, Fuzzy Rules

Abstract

The Intrusion Detection System (IDS) can be employed broadly for safety network. Intrusion Detection Systems (IDSs) are commonly positioned alongside with other protecting safety mechanisms, such as authentication and access control, as a subsequent line of defence that guards data structures. In this paper, Adaptive Neuro Fuzzy Inference System has utilized to predict the risk severity of the malicious nodes found the previous classification phase.

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Published

04-01-2019

How to Cite

Dharmarajan, R., & Thiagarasu, V. (2019). Computation of Risk Severity of the Malicious Node using Adaptive Neuro Fuzzy Inference System (ANFIS). Asian Journal of Engineering and Applied Technology, 8(1), 9–14. https://doi.org/10.51983/ajeat-2019.8.1.1067