Arash Moradzadeh
Arash Moradzadeh
Thesis area: Cyber Physical security of power systems
Supervisor: Prof. Behnam Mohammadi-Ivatloo
Abstract: Modern power and energy systems have become a typical cyber physical system (CPS), where reliable and stable automation control process is heavily depending on the accurate monitoring and measurement data. Cyber Physical Systems (CPS) are considered to be important and fundamental components of the Internet of Things (IoT). As can be seen, these systems will play a significant role in power and energy systems with their significant advances from now on. The CPS are based on a combination of cyber and physical systems. Optimal use of energy, awareness of the global situation and improving the quality of services, increasing the accuracy of efficiency and real-time performance of smart applications and services are the essential role of the CPSs. However, the integration of the CPS increases the vulnerabilities of critical power infrastructures. In some cases, these systems inevitably suffer from cyber security vulnerabilities, and cyber-attacks related to communication networks and smart devices. The cyber-attacks on the CPS can manipulate the measurement data and mislead the control system to make incorrect operational decisions. Also, once the malicious attackers take the substation control authorities, they can disrupt and interrupt all activities related to the transmission and distribution of energy. Therefore, it is critical to properly choose the reclosing time to mitigate these impacts and measures to anticipate these attacks. Data mining applications such as the machine learning and manifold learning techniques due to their high capabilities in data processing and accurate prediction applications can be a suitable solution for detecting and even prognosis the cyber-attacks in power and energy systems. Accordingly, in this research, a hybrid model of machine learning and manifold learning applications is presented and employed to prognosis and control various types of cyber-attacks in energy and power systems.
Publications in journals and conference papers may be found at Publications Page or Google Scholar.