Heuristic Detection Network; An Adaptive DDoS Control

Distributed denial of service (DDoS) is a crucial problem of dynamic and stochastic task environment. Most existing DDoS studies are designated for the fixed infrastructure networks. In practice, the majority of the solutions have adopted centralized defensive design and implementation strategies. In this research, a means of adaptation to DDoS detection and control is proposed as a key entity of the study with an generic event driven model for attack tree discovery and adaptive flood control algorithms without transport layer dependency. The proposed method is discussed as a Q function based learning detection. In addition, a scalable DDoS detection framework is advocated. The design and implementation of the proof of concept are deliberated.