• Monika K C
• Chaithra R
• Fariya N
• Mr. Kushal Kumar BN

In recent years, Microgrids are involved in Communication and Information Technology, and recognized as an important unit of Internet of Things (IoT). A number of CII which is Critical Information Infrastructure systems are relying on these technologies. This dependency of microgrids makes them prone to malicious cyberattacks, which can create major technical, economic, social and control problems in power network systems. Detection of cyber-attacks with high accuracy is a challenge. In microgrids, the Advanced Metering Infrastructure (AMI) is developed to monitor and control the grid for stable and efficient operation. The AMI is vulnerable to cyberattacks. Many research efforts are going on detecting such attacks. This paper performs a survey on various algorithms implemented to detect data integrity attacks and anomaly attacks that happen during transmission in a microgrid.

Smart grids, Cyberattack, Advanced Metering Infrastructure (AMI), Machine learning, Anomaly attack.

"An Anomaly Attack Detection Model in Microgrids using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.g385-g387, March-2022, Available :http://www.jetir.org/papers/JETIR2203652.pdf

"An Anomaly Attack Detection Model in Microgrids using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppg385-g387, March-2022, Available at : http://www.jetir.org/papers/JETIR2203652.pdf