Machine Learning for Future Fiber-Optic Communication Systems

Chapter Ten: Machine learning for network security management, attacks, and intrusions detection

Marija Furdek; Carlos Natalino    Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

Abstract

This chapter focuses on challenges, progress and pitfalls in applying ML to physical-layer security management. In the context of trustworthy networks, we motivate the need for automation in support of the work of network security professionals. We summarize the characteristics of known attack techniques targeting the physical layer and outline the framework for optical network security management. Supervised, semisupervised and unsupervised learning techniques that can aid automation of network security management are ...