Analysis of Cyber-Physical Threats in power grid

Supervisor: Dr Feras Alasali

Students: Mohammad Azmi Abudayyeh · Enas Yousef · Dua'a Rumaneh · Bashar Aldeiri · Tariq AlJadayah

Abstract: Due to the use of cutting-edge communication, control, and computing methods, smart and modern grids are at a higher risk of cyber-attacks. In our project, we aim to analyze the impact of cyber-physical threats on the power network at the MV/LV level. Specifically, we seek to demonstrate the severity of these threats and their potential to cause network outages. The extent of the damage caused by such attacks depends on the stability and resilience of the cyber-infrastructure. A successful attack on critical infrastructure can have disastrous effects on the economy, natural resources, and human safety. Consequently, our research focuses on investigating cyber-physical threats, which are crucial to data network planning and are among the top concerns in smart grid security.

Cyber-Physical Security Smart Grid Technologies Machine Learning

Cyber-Physical Threats on Smart Home

Supervisor: Dr Feras Alasali

Students: Zaid Aldaraghmeh · Moumen Zaree · Yazan Shawer · Fayiz Saleh · Abdallah Thaher

Abstract: Smart home systems have gained immense popularity in recent years due to their ability to automate and simplify everyday tasks such as managing lighting, heating, and security. However, the rising dependence on technology in homes has led to growing apprehension about the security of these systems. Physical and electrical cyber-attacks on smart home systems can have severe consequences, including unauthorized access to personal data, control of home systems, and physical harm to occupants. The aim of this study is to analyze the impact of such attacks on the electrical system of smart homes, highlighting the potential risks associated with them.

Cyber-Physical Security Smart Grid Technologies Machine Learning