Securing Software Defined Networking Using Intrusion Detection System - A Review

For the time being, the advances of the Internet technologies in respect of a wide-spread development and the fixed nature of traditional networks have the restricted capacity to satisfy organizational business requirements. Software-Defined Networking (SDN) as a new network architecture presented to overcome these challenges and issues of the existing network topologies and provide peculiar features. However, these programmable and centralized architectures of SDN suffer from new security threats, which require innovative security approaches and techniques such as Intrusion Detection Systems (IDSs). Currently, most of the IDS of SDN are implemented with a machine learning method; however, a deep learning method is also being utilized to satisfy better detection performance. Still, no recent comprehensive review of IDS has been conducted; therefore, this article provides an inclusive and detailed overview and analysis of the SDN with its security issues and attacks and IDS-based on deep learning as a solution for the security issue, to highlight their strengths and weaknesses, and then derive future research directions from these shortcomings.