Survey on SDN based network intrusion detection system using machine learning approaches

• Published in: Peer-to-peer networking and applications Vol. 12; no. 2; pp. 493 - 501
• Main Authors: Sultana, Nasrin, Chilamkurti, Naveen, Peng, Wei, Alhadad, Rabei
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2019; Springer Nature B.V
• Subjects: Artificial intelligence; Challenges and Prospective Smart Solutions; Communications Engineering; Computer Communication Networks; Computer networks; Cybersecurity; Engineering; Environment models; Information Systems and Communication Service; Intrusion detection systems; Machine learning; Networks; Signal,Image and Speech Processing; Software-defined networking; Special Issue on Software Defined Networking: Trends; Deep learning; SDN; NIDS; Machine learning

Software Defined Networking Technology (SDN) provides a prospect to effectively detect and monitor network security problems ascribing to the emergence of the programmable features. Recently, Machine Learning (ML) approaches have been implemented in the SDN-based Network Intrusion Detection Systems...