Cyber security of the smart grid: Attack exposure analysis, detection algorithms, and testbed evaluation

Abstract

<p>While smart grid technologies are deployed to help achieve improved grid resiliency</p> <p>and efficiency, they also present an increased dependency on cyber resources which may</p> <p>be vulnerable to attack. This dissertation introduces three components that provide new</p> <p>methods to enhancing the cyber security of the smart grid.</p> <p>First, a quantitative exposure analysis model is presented to assess risks inherited</p> <p>from the communication and computation of critical information. An attack exposure</p> <p>metric is then presented to provide a quantitative means to analyze the model. The</p> <p>metric's utility is then demonstrated by analyzing smart grid environments to contrast</p> <p>the effectiveness of various protection mechanisms and to evaluate the impact of new</p> <p>cyber vulnerabilities.</p> <p>Second, a model-based intrusion detection system is introduced to identify attacks</p> <p>against electric grid substations. The system expands previous research to incorporate</p> <p>temporal and spatial analysis of substation control events in order to differentiate attacks</p> <p>from normal communications. This method also incorporates a hierarchical detection</p> <p>approach to improve correlation of physical system events and identify sophisticated</p> <p>coordinated attacks.</p> <p>Finally, the PowerCyber testbed is introduced as an accurate cyber-physical envi-</p> <p>ronment to help facilitate future smart grid cyber security research needs. The testbed</p> <p>implements a layered approach of control, communication, and power system layers while</p> <p>incorporating both industry standard components along with simulation and emulation</p> <p>techniques. The testbed's efficacy is then evaluated by performing various cyber attacks</p> <p>and exploring their impact on physical grid simulations.</p>