## 1 Introduction
Data from research that have been published that deal with SG are shown in Figure 2.  
Figure 1: Components of a power grid that houses electrical support systems [2,3]. * [10] DoS/DDoS attacks Some of the hacking techniques covered in this article are traffic analysis, social engineering, scanning IP addresses, monitoring ports, scanning vulnerabilities, worms, Trojan horses, DoS, FDI, replay, privacy violations, integrity violations, backdoors, MITM, jamming, popping the HMI, and masquerade. Various forms of online attacks on confidentiality, integrity, availability, authorization, and authenticity. MITM, jamming, FDI, spoofing, DoS, malware, replay attacks. Attacks of various forms launched against energy corporations, renewable energy resources, and metering networks. Major cyberattacks against the smart grid and the effects have various security approaches to solve the cyber-security problem in smart grids. The most commonly encountered challenges when dealing with smart homes and smart grids. A variety of cyberattack situations, each with its unique defensive measures. Strategies to protect against or avoid the occurrence of cyberattacks. Multiple cyberattacks have been directed at smart grids and the security systems used. Vulnerabilities in the traditional electricity network that cyberattacks can target. In the case of smart grid metering networks, security, and privacy criteria must be addressed research in the future, including its trends and problems. \begin{table}
\begin{tabular}{c c c} \hline \hline
**References** & **Cyberattacks** & **Objectives** \\ \hline
[10] & Multiple cyberattacks were launched targeting the CIA computers and the five OSI communication layers. & The various forms of cyberattacks and the over-all necessity of taking prevention achievement. An analysis of multiple cyberattacks, including the requirements for their protection, as well as the directions for the future. Cyber-physical security of smart grids and potential attack scenarios based on information technology. Methods of prevention and detection, as well as the difficulties involved, concerning the threats posed by smart grids. Critical cyber-physical attacks and the various ways to defend against them. Investigating the effects of combined cyber and physical attacks on smart grids. The smart grid and all of its core elements. Methods now in use for various communication protocols and their underlying systems Attacks of the DoS and DDoS variety, and the effects they have on smart grids. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Existing Surveys Related to the Cyber-security of Smart grids. Figure 2: Publication statistics on SG [8]. Machine learning, deep learning, Data mining, evolutionary algorithms, fuzzy logic, and other similar techniques are all included in artificial intelligence. Machine learning is becoming increasingly important to researchers for danger detection. The authors of [16] used machine learning methods such as random forest, support vector machine, and neural networks to recognize jamming attacks. Their numerical tests show that the suggested random forest strategy works well. The authors employed machine learning techniques to identify social engineering attacks. The system uses unsupervised learning, so it doesn't need to be familiar with cyberattacks to recognize them. The authors examined different machine learning applications' accuracy, speed, and consistency. They discovered that support vector machines outperform competing strategies using computer simulations [17]. The authors of [18] used machine learning methods to protect against network-layer brute force attacks on the Secure Shell protocol. The authors developed scalable detection models with the help of classifiers like K-Nearest Neighbors decision trees and Naive Bayes that may be effective at making predictions. The author of [19] describes a different experiment that utilized machine learning.