Cyber-Physical Security in Smart Grids: A Holistic View with Machine Learning Integration

Cyber-physical attacks are become more challenging in each passing days owing to the continuous advancement of smart-grid systems. In the present industrial revolution, the smart grid is integrated with a wide-range of technologies, equipment/devices and tools/software to make the system more trustworthy, reliable, efficient, and cost-effective. Regardless of achieving these objectives, the peril area for the critical attacks has also been stretched owing to the add-on cyber-layers. In order to detect and mitigate these attacks, the machine learning (ML) tools are being reliably and massively used. In this chapter, the authors have reviewed several state-of-the-art related researches comprehensively. The advantages and disadvantages of each ML based schemes are identified and reported in this chapter. Finally, the authors have presented the shortcomings of the existing researches and possible future research direction based on their investigation.