Multilayer Cyberattacks Identification and Classification Using Machine Learning in Internet of Blockchain (IoBC)-Based Energy Networks.
Description
• 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.
Files
Institutions
- Skyline University CollegeSharjah, Sharjah
- Vaasan YliopistoVaasa