Distributed Denial-of-Service Attack by SVM and KNN using Hybrid Machine Learning Techniques

Abstract

DDoS attacks are primary concern in internet security today. A distributed denial-of-service is a malicious attempt to disrupt normal traffic of a targeted server, service or network by overwhelming the target or its surrounding infrastructure with a flood of internet traffic. DDoS attacks achieve effectiveness by utilizing multiple compromised computer system as sources of attack traffic. DDoS attacks in ICMP protocol is called as ICMP flood attack where the attacker attempts to overwhelm a targeted device with ICMP echo-request packets, causing the target to become inaccessible to normal traffic. This type of attack is also known as Ping(ICMP) Flood attack.Fast detection of the DDoS attack, quick response mechanisms and proper mitigation must be done. An investigation has been performed on DDoS attack and it analyzes the details of its phase using machine learning technique to classify the network status. In this paper, we propose a hybrid KNN-SVM method on classifying, detecting and predicting the DDoS attack.