Cyber-Physical Energy Systems Security: Threat Modeling, Risk Assessment, Resources, Metrics, and Case Studies

Abstract

Cyber-physical systems (CPS) are interconnected architectures that employ analog, digital, and communication resources for their interaction with the physical environment. CPS are the backbone of enterprise, industrial, and critical infrastructure. Thus, their vital importance, makes them prominent targets for malicious attacks aiming to disrupt their operations. Attacks targeting cyber-physical energy systems (CPES), given their mission-critical nature, can have disastrous consequences. The security of CPES can be enhanced leveraging testbed capabilities to replicate power systems operation, discover vulnerabilities, develop security countermeasures, and evaluate grid operation under fault-induced or maliciously constructed scenarios. In this paper, we provide a comprehensive overview of the CPS security landscape with emphasis on CPES. Specifically, we demonstrate a threat modeling methodology to accurately represent the CPS elements, their interdependencies, as well as the possible attack entry points and system vulnerabilities. Leveraging the threat model formulation, we present a CPS framework designed to delineate the hardware, software, and modeling resources required to simulate the CPS and construct high-fidelity models which can be used to evaluate the system's performance under adverse scenarios. The system performance is assessed using scenario-specific metrics, while risk assessment enables the system vulnerability prioritization factoring the impact on the system operation. The overarching framework for modeling, simulating, assessing, and mitigating attacks in a CPS is illustrated using four representative attack scenarios targeting CPES. The key objective of this paper is to demonstrate a stepby-step process that can be used to enact in-depth cybersecurity analyses, thus leading to more resilient and secure CPS.

Towards a Secure and Resilient All-Renewable Energy Grid for Smart Cities

“…The objective towards achieving a secure and resilient 100% renewable energy grid requires the development of multi-layer control and system methods, ranging from system stability controls to secure co-design of hardware/software/physical systems, that contribute towards a holistic cyberphysical energy system (CPES) integrated within smart cities [5]. The technological dimensions that will characterize those smart cities are electricity grids and the information and communication networks that can contribute in the development of intelligent transportation systems and support clean energy (e.g., electric vehicles, energy-efficient buildings, etc.).…”

Data‐driven operation of the resilient electric grid: A case of COVID‐19

“…This is a real challenge both for operators to deal with and for implemented ML algorithms. However, currently, load-changing attacks are not a real problem: "Although currently hypothetical, due to the low penetration rates of IoT-controllable high-wattage loads and DERs, load-changing attacks are projected to become a 'real' threat in the near future as the number of controlled DERs and loads is anticipated to grow exponentially" [137]. Therefore, the sudden drop in load demand was not expected to be a cyberattack.…”

“…Therefore, the sudden drop in load demand was not expected to be a cyberattack. Some of the research attempts to address load-changing attacks through formulating the problem mathematically are [67,137]. Ospina et al [67] discuss the feasibility of load-changing attack during the COVID-19 pandemic.…”

“…Ospina et al [67] discuss the feasibility of load-changing attack during the COVID-19 pandemic. ML approaches for detecting cyberattacks are discussed in the next part of our paper and some references are provided in [137]. However, distinguishing the sudden drop in demand due to COVID-19 and cyberattack is a challenge that needs to be addressed.…”

The intersection of Artificial Intelligence and cybersecurity: Challenges and opportunities

“…In essence, the emergence of AI as a game-changer in cybersecurity represents a fundamental shift in the way we approach cyber defence. By leveraging the power of intelligent automation and data-driven decision-making, AI enables defenders to stay one step ahead in the perpetual cat-and-mouse game of cybersecurity, levelling the playing field against increasingly sophisticated adversaries [15], [24]. As organizations continue to embrace AI-driven security solutions, they stand poised to bolster their resilience against evolving cyber threats and safeguard their digital assets with unprecedented efficacy and efficiency.…”