Detection of DDoS Attacks in Software Defined Networking Using Entropy

Fan, Cong and Kaliyamurthy, Nitheesh Murugan and Chen, Shi and Jiang, He and Zhou, Yiwen and Campbell, Carlene (2021) Detection of DDoS Attacks in Software Defined Networking Using Entropy. Applied Sciences, 12 (1). e370. ISSN 2076-3417

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Abstract

Software Defined Networking (SDN) is one of the most commonly used network architectures in recent years. With the substantial increase in the number of Internet users, network security threats appear more frequently, which brings more concerns to SDN. Distributed denial of Service (DDoS) attacks are one of the most dangerous and frequent attacks in software defined networks. The traditional attack detection method using entropy has some defects such as slow attack detection and poor detection effect. In order to solve this problem, this paper proposed a method of fusion entropy, which detects attacks by measuring the randomness of network events. This method has the advantages of fast attack detection speed and obvious decrease in entropy value. The complementarity of information entropy and log energy entropy is effectively utilized. The experimental results show that the entropy value of the attack scenarios 91.25% lower than normal scenarios, which has greater advantages and significance compared with other attack detection methods.

Item Type: Article
Additional Information: ** From MDPI via Jisc Publications Router ** History: accepted 28-12-2021; pub-electronic 31-12-2021. ** Licence for this article: https://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords: software defined networking, entropy, distributed denial of service attacks
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Institutes and Academies > Wales Institute for Science & Art (WISA)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 05 Jan 2022 12:00
Last Modified: 05 Jan 2022 12:00
URI: https://repository.uwtsd.ac.uk/id/eprint/1873

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