Distributed Denial Of Service Attack Detection A Hybrid Intelligent System Approach

The occurrence of distributed denial of service (DDoS) attacks has become more frequentrnin today’s network environment. Detecting these attacks would prevent the unnecessaryrnutilization of resources which otherwise could have been used to service legitimate users.rnThis requires the implementation of an effective DDoS detection system. Manyrnresearches have proposed a number of DDoS detection systems and one of the recentrnideas is to use the hybrid intelligent systems for the effective detection of DDoS attacks.rnIn this work, adaptive neuro-fuzzy inference system (ANFIS) has been used as the hybridrnintelligent system for the detection of DDoS attacks. An experimental environment hasrnbeen setup to collect the normal and attack traffic data for training and testing purposes.rnA detection system has been proposed having ANFIS as its detection core. The proposedrnsystem has been tested in the detection of TCP SYN flooding attack. It is found thatrnANFIS is able to classify the TCP SYN DDoS data with very good precision.

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