A Study On Detection Of Distributed Denial Of Service Attacks Using Machine Learning Techniques

Abstract

Distributed Denial of Service (DDoS) attacks is a serious threat to the network security. Servers of many companies have been the victims of such novel type of attacks. In a short span of time, these attacks from the multiple bots controlled by the botmaster (cracker) can easily drain the computing and communication resources of the victim. As the attacker uses the spoofed IP address and therefore cracker leaves the botnet quickly after it executes the command, therefore detecting the attacker is extremely difficult.