A Multi-Agent Intelligence Hybrid System Technique for Detection and Defense of DDoS Attacks

In the paper, we propose the distributed detection and identification multi-agent system (DDIMAS) framework that is the first attempt to apply in solving distributed denial of service (DDoS) problem. It includes three stages which are information heuristic rule, meta-heuristic algorithm and backward and forward search (BFS) rule, respectively. Moreover, the framework is a flexible architecture that can incorporate into other algorithms or rules to improve the overall performance. From the evaluation design, the experiment results show that our method is with higher detection rate and better accuracy than standard repositories. The proposed framework resolves issues in other swarm optimization algorithms and reveals that the performance of DDIMAS is better than existing methods and the adaptive meta-heuristic algorithm framework outperforms other methods for detecting DDoS attacks.