Intrusion Detection, Forecast and Traceback Against DDoS Attacks
Nowadays, DDoS is one of the most troublesome attacks. Attackers often penetrate innocent routers and hosts to make them unwittingly participate in such large-scale attacks acting as zombies or reflectors. Also, the Internet consists of autonomous network management units. Organizing these units is helpful in detecting DDoS attacks if several adjacent or nearby network management units could collaboratively guard and protect their important surrounded neighbors. This paper proposes an Intrusion Detection, Forecast and Traceback System (IDeFT) based on united defense environment. First, a detection system that is able to detect two types of attacks, logical and DoS/DDoS, is developed. Logical attacks are recognized by neural networks.