An ANFIS-Based framework DDoS attack

Abstract

Purpose: In this paper, a simulation environment is set-up to generate distributed denial of service data in Virtual Knowledge Community (VKC) in order to study the pattern of attack in multi-agent environment. Design/Methodology/Approach: A threshold approach is used to construct the profile of the traffic for the agents in the network, and to identify anomalies whenever traffic goes out of profile. An Adaptive Neuro-Fuzzy Inference System (ANFIS) is used in classifying attack type and to determine its location. Four ANFIS are trained and tested in this research work to provide attack detection and classification. Findings: An Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to categorise the datasets into attack and normal traffic using some standardized threshold values. Research limitations:/Implications: The study is only limited to detecting distributed denial of service attack in multi-agent environment. Practical Implications: The experiment and the simulation are carried out in a computer laboratory using Java Agent Development Framework and Adaptive Neuro-Fuzzy Inference System. Originality: An adaptive security is implemented in this study for detecting distributed denial of service attack in an agent-based virtual knowledge community.