ERI: Multi-Layer Dynamic Strategic Decision-Making for Integrated Cyber-Physical Energy Systems Security and Resilience

Fordham University, Bronx NY

Investigators

Abstract

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The pervasive adoption of advanced information and communication technologies (ICTs) in electric power systems has made the grid a complex cyber-physical energy system (CPES). Among the ICTs, the Internet of Things (IoT) plays a crucial role in filling the gap between the control and monitoring of electricity services and physical grid dynamic processes. The widespread implementation of IoT devices significantly improves the CPES's operational performance, but it also exposes the grid to vast cyber threats. It has been revealed that the adversary can disrupt the CPES operations through IoT botnet attacks by compromising a large number of IoT-operated energy devices in the power distribution system and using them as a means to launch a coordinated cyber-physical attack. Classical approaches to trustworthy CPES focus on improving cybersecurity to prevent attacks or enhancing physical resiliency to restore the system operation after attacks. However, solely relying on either approach is not a viable solution as achieving perfect security or resiliency is extremely cost-prohibitive, if not impossible. To this end, this project aims to devise cost-effective and holistic mechanisms for enhancing both the security and resiliency of CPES under large-scale IoT botnet attacks. The design paradigm will jointly mitigate the risks of the cyber components and equip the physical grid with agile recovery capability. The project will develop a unified theoretical framework to facilitate grid operators' decentralized, strategic, and integrative decision-making on security and resiliency strategies in CPES. Specifically, the project will first establish a quantitative framework for analyzing the systemic cyber-physical risks imposed by the massive IoT-controlled energy devices in the microgrid. This systemic risk model will then be integrated with the microgrid's operation framework to study the attacker's strategic behavior in destabilizing the grid. The adversarial analysis facilitates uncovering the most vulnerable locations in the microgrids, which is leveraged to guide the strategic defense. The second research thrust will establish a dynamic game to enable the integrated design of proactive cyber defense and physical resiliency planning strategies for networked microgrids. The multi-layer multi-stage game-theoretic design provides preventive security mechanisms to harden the cyber components of CPES and corrective resiliency measures to improve the preparedness of the physical grid for attacks. The project will further develop distributed learning-based mechanism for the microgrid operators to counteract the strategic adversaries adaptively. The developed techniques and results in this project will be demonstrated using public power system simulation tools. The PI will integrate the research outcomes into the engineering, data science, and cybersecurity curriculum, providing students cross-disciplinary training in cyber-physical smart grids, security and resilience, and artificial intelligence. The PI is also committed to public education through outreach activities to further broadening the participation of undergraduate and graduate students in the project. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.