Intelligent Inter and Intra Network Traffic Estimation Technique for DDoS Attack Detection using Fuzzy Rule Sets for QoS Improvement

Abstract

The quality of service of any network has higher dependency at throughput, latency and service completion strategies. In modern communication systems, there are many loopholes, which could be used by some malicious users to perform various network attacks so that the performance of the network is degraded. There are many denial of service when an approach has been discussed towards the problem of network threats, but still suffers the quality of denial of service attack detection. Propose a service-constrained approach learns the network traffic in various ways like the traffic incurred within the network and that comes from external network. The method uses various features like hop count, hop details, payload, TTl, time and so on. To maintain a rule set with fuzzy value where each rule specifies the feature of genuine packet being received. The incoming packet has to meet any of the rules and the attribute of the packet has to lie between the ranges of values in the rule. The proposed method estimates the inter traffic and intra traffic through the routes of the packet being transferred to identify the genuine nature of the packet being received. In addition, the method maintains set of logs where the packet features are stored to compute the legitimate weight of each packet being received. Based on compute inter and intra traffic values the received packets trustworthy is computed to allow or deny the packet. The proposed method increases the accuracy of DDOS attack detection and helps to improve the performance of the network.
DOI: 10.17762/ijritcc2321-8169.150851