Title: A novel deviation-based detection mechanism for DDoS attacks in the cloud environment

Authors: A. Somasundaram; S. Devaraju

Addresses: Department of Computer Applications, Sri Krishna Arts and Science College, Coimbatore, India ' School of Computing Science and Engineering (SCSE), VIT Bhopal University, Bhopal, India

Abstract: Distributed denial-of-service attacks are prevalent vulnerabilities in cloud computing, causing disruption to legitimate users. Despite existing detection methods, reliability and accuracy need improvement. A systematic approach is urgently needed for both spoofing and non-spoofing attacks. To distinguish attacks from legitimate network traffic, this paper proposes a deviation-based detection mechanism based on software-defined networks. The model has two significant phases such as knowledge acquisition and deviation-based detection. The model makes use of the variance of a discrete probability distribution on the network features that are used to collect the knowledge base. For the known flow, the deviation between the traffic and the knowledge base is evaluated to determine the attack traffic. The rule-based detection mechanism is proposed for detecting attacks in the unknown flow. The proposed model, analysed through experimental analysis, demonstrated an average detection rate of 98% and an execution time of 0.72 seconds, outperforming its competitors.

Keywords: DDoS attack; cloud environment; attack detection; variance; discrete probability distribution; traffic representatives.

DOI: 10.1504/IJICS.2025.148458

International Journal of Information and Computer Security, 2025 Vol.28 No.1, pp.51 - 72

Accepted: 17 Oct 2024
Published online: 05 Sep 2025 *