Cyber-related risk assessment and critical asset identification within the power grid

Abstract

This paper introduces a new way to detect and improve the vulnerability of bulk power systems against the intrusion and malicious acts of cyber hackers. For this aim, detecting the most vulnerable part of the power grid to hacker attack is needed. The method for finding the most vulnerable substation inside the grid (fist pass model) and then finding the most critical asset inside that substation (second pass model) is presented. The suggested method performs Improvement in overall vulnerability of the grid by calculating the risk of each asset and placing a security agent on the most vulnerable positions within the substation to prevent the cyber attacks as most as possible.