  Smart grid (SG) is a complex cyber-physical system that utilizes modern cyber
and physical equipment to run at an optimal operating point. Cyberattacks are
the principal threats confronting the usage and advancement of the
state-of-the-art systems. The advancement of SG has added a wide range of
technologies, equipment, and tools to make the system more reliable, efficient,
and cost-effective. Despite attaining these goals, the threat space for the
adversarial attacks has also been expanded because of the extensive
implementation of the cyber networks. Due to the promising computational and
reasoning capability, machine learning (ML) is being used to exploit and defend
the cyberattacks in SG by the attackers and system operators, respectively. In
this paper, we perform a comprehensive summary of cyberattacks generation,
detection, and mitigation schemes by reviewing state-of-the-art research in the
SG domain. Additionally, we have summarized the current research in a
structured way using tabular format. We also present the shortcomings of the
existing works and possible future research direction based on our
investigation.
