Survey on Wireless Sensor Network Attack Detection using Machine Learning Approach

This study discusses about the incorporation of cybersecurity in smart microgrids and develops a novel architecture for detecting and preventing data integrity attacks on smart grid based wireless sensor networks (WSN). Intelligent systems that use computer-based algorithms to manage or monitor networking and communication mechanisms are known as cyber physical systems. Due to the existing challenges in cyber system, any cyber incident may have an adverse impact on their economic and physical activity. Power electronics-based smart microgrids are particularly vulnerable to cybe r-attacks due to their inability to change and results in potential consequences in terms of operation and stability. The cyber-physical systems of smart microgrids are briefly analyzed in this research study. The paradigm for detecting cyber-attacks on wireless sensor networks is also explained. Considering that, a Fake Data Injection (FDI) attack undermines the data integrity in one of the most significant threats to smart micro grids is the cyber/communication network, which is thoroughly examined in this study. This study also examines how FDI attacks on smart micro grids physically, economically, and technically. This research study gives illustrations on the design and detection of FDI attacks in intelligent micro grids. Both critical smart grid cyber-security requirements and examples of existing international cyber-security initiatives are provided. The topic of future cyber-security developments in smart microgrids is then examined.