Machine learning techniques for Secure Edge SDN

Maleh, Yassine, Sahid, Abdelkebir, Abd El-Latif, Ahmed A. and Ouazzane, Karim (2024) Machine learning techniques for Secure Edge SDN. In: Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities. EAI/Springer Innovations in Communication and Computing . Springer International Publishing, Cham, Switzerland, pp. 175-193. ISBN 9783031510977

Abstract

Software-defined network (SDN) makes today's networks programmable and provides several benefits such as global awareness, centralized management, and network abstraction. SDN is an innovative paradigm that enables the development of new and more efficient security services. This chapter provides an overview of the software-defined networking paradigm. The challenge of this chapter is twofold: On the one hand, to study and explore the contribution of SDN to security to design efficient solutions that will mitigate several attack vectors and on the other hand, to protect SDN against these attacks, by analyzing mitigation techniques based on machine learning.

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