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Swarm intelligence based autonomous DDoS attack detection and defense using multi agent system


In the recent developments in the cloud computing made it’s accessible by everyone and millions of people daily store their data in the cloud platform and utilize for various kind of need. In this situation, the common issue in the day-to-day usage is DDoS attack, which severally affects the availability of the resources or services. In this paper a new method is proposed to detect and defend against the DDoS attacks using autonomous multi agent system and the agents use the particle swarm optimization among themselves to have strong communication and accurate decision making. DDoS attacks are detected using the multiple agents that communicate with each other and updates the coordinator agent. The current scenario is analyzed by the coordinator agent using the entropy and covariance methods to check for the DDoS attacks. During this stage the monitoring agent will be in live and keeps eye on the cloud resources and networking. If anything happens abnormal it triggers the detection and recovery agents to act. The experimental result shows this proposed system gives the optimized performance and improved security in the cloud platform.

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Correspondence to R. Kesavamoorthy.

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Kesavamoorthy, R., Ruba Soundar, K. Swarm intelligence based autonomous DDoS attack detection and defense using multi agent system. Cluster Comput 22 (Suppl 4), 9469–9476 (2019).

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  • Cloud computing
  • DDoS attack and detection
  • Multi agent system
  • Swarm intelligence