Spyrou, E.D.; Tsoulos, I.; Stylios, C. Distributed Denial of Service Classification for Software-Defined Networking Using Grammatical Evolution. Future Internet2023, 15, 401.
Spyrou, E.D.; Tsoulos, I.; Stylios, C. Distributed Denial of Service Classification for Software-Defined Networking Using Grammatical Evolution. Future Internet 2023, 15, 401.
Spyrou, E.D.; Tsoulos, I.; Stylios, C. Distributed Denial of Service Classification for Software-Defined Networking Using Grammatical Evolution. Future Internet2023, 15, 401.
Spyrou, E.D.; Tsoulos, I.; Stylios, C. Distributed Denial of Service Classification for Software-Defined Networking Using Grammatical Evolution. Future Internet 2023, 15, 401.
Abstract
Software-Defined Networking (SDN) is a network implementation paradigm of great importance, as it has a profound impact on the pace of technological progress. While SDN doesn’t directly address the technical complexities of routing, congestion control, traffic engineering, security, mobility, reliability, or real-time communication, it paves the way for innovative solutions to emerge for these and similar challenges. Security is of utmost importance in SDN with Distributed Denial of Service (DDoS) being an attack which creates large scale problems. DDoS creates malicious traffic that resembles normal traffic in order to create service problems. As such, mechanisms that distinguish between benign and malicious traffic is essential, since this is the first step to mitigate the problem of DDoS. In this paper, we take a dataset onboard which exhibits benign and malicious traffic in SDN. There are 23 features that are used for classification purposes. Here we utilise classification procedure based on three methods based Grammatical Evolution applied on the aforementioned data. We provide results that show the efficiency of our approach and show that all three methods exhibits satisfactory results.
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
