Multilayer Cyberattacks Identification and Classification Using Machine Learning in Internet of Blockchain (IoBC)-Based Energy Networks.

• The data provides insights into cyberattacks, helping in the development of predictive models that can anticipate future threats and vulnerabilities in energy and power systems.
• Data analysis helps in customizing security protocols and measures tailored to specific threats and vulnerabilities in distributed energy systems, enhancing overall system security.
• Data contributes to a better understanding of the current security posture of the energy and power systems, aiding in strategic decision-making and resource allocation for cybersecurity.
• Cybersecurity and smart grid agencies, along with other stakeholders, can leverage these datasets to develop a more intelligent and resilient data exchange network. This forward-thinking strategy will help in identifying and mitigating different types of cyberattacks, ensuring the protection of the confidentiality of employees, companies, and clients.