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SECURE AND RESILIENT OPERATION OF CYBER-PHYSICAL POWER SYSTEMS
Title
SECURE AND RESILIENT OPERATION OF CYBER-PHYSICAL POWER SYSTEMS
Creator
Li, Zhiyi
Date
2017, 2017-07
Description
For economic reasons, modern power systems are commonly operated close to their secure limits so that they are vulnerable to unexpected severe...
Show moreFor economic reasons, modern power systems are commonly operated close to their secure limits so that they are vulnerable to unexpected severe disruptions such as disastrous cyberattacks and extreme weather events. This thesis is aimed at enhancing the security and resilience of power supplies for facilitating the development of a Smart Grid, when power systems in various parts of the world have been undergoing transitions toward cyber-physical systems. First, this thesis discusses common cybersecurity vulnerabilities in modern power systems and presents physical implications of cyberattacks on power system operations. In particular, this thesis analyzes a specifc type of coordinated cyberphysical attacks that could lead to undetectable line outages. Coordinated with physical attacks causing line outages, cyberattacks comprising topology preserving and load redistribution attacks could mask and potentially exasperate the outages to trigger cascading failures. Such coordinated cyber-physical attacks are analyzed in a bi-level optimization model which is then transformed into a mixed-integer linear programming problem. The proposed model and the two-stage solution algorithm are examined by case studies based on the IEEE 14-bus and 118-bus test systems. Second, this thesis offers the pertinent studies on quantifying the risk of cybersecurity vulnerabilities in power system operations. A type of locally coordinated cyber-physical attacks is analyzed in detail, which would cause undetectable line outages in local areas without the need for complete network information. A risk-based optimization model in the mixed-integer linear programming form is presented for analyzing physical implications resulting from the power ow redistribution. An efficient greedy search-based heuristic method is then developed to offer satisfactory solutions for real-time applications, which are verified by case studies based on a six-bus system and the two-area IEEE RTS-96 system. Third, this thesis studies security measures for mitigating the cybersecurity risk in power system operations. A game-theoretic framework is built for determining the optimal combination of security measures based on the minimax-regret decision rule. The resulting multi-level optimization model is reformulated as a bilevel mixed-integer linear programming problem. An implicit enumeration algorithm is then developed to achieve an exact solution to this complex problem. Acceleration techniques are also provided to improve the computation efficiency for large-scale power system applications. The proposed model and solution methods are validated by case studies based on a six-bus test system and the two-area RTS-96 system. Fourth, this thesis extends the discussion of cybersecurity vulnerabilities to the operation of distributed power systems like microgrids. Since microgrids are regarded as building blocks of a Smart Grid, they strive for cyber-secure operations for sustaining power services to local customers. The assessment and mitigation of the cybersecurity risk in microgrid operations is then presented in depth. Additional opportunities provided by software-defined networking technologies to enhance the microgrid cybersecurity are also realized by the proposed defense-in-depth framework that comprises three lines of defense against cyberattacks. Last, this thesis investigates the role of networked microgrids in enhancing the power system resilience against extreme events. Since resilience is an intrinsically complex property which requires deep understanding of power system operations, a generic simulation-based framework is developed for power system operators to analyze the resilience comprehensively and respond effectively in emergency conditions. The notion that the deployment of networked microgrids catalyzes the resilience enhancement in a Smart Grid is discussed in detail. Besides, the management of networked microgrids for achieving a higher degree of resilience, reliability, and efficiency of power supplies is discussed based on the proposed hierarchical control framework.
Ph.D. in Electrical Engineering, July 2017
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Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Title
Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Creator
Arnold, David James
Date
2024
Description
Digitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To...
Show moreDigitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To achieve these gains, the Internet of Things (IoT) has become an integral component of network infrastructures. However, integrating embedded devices expands the network footprint and softens cyberattack resilience. Additionally, legacy devices and improper security configurations are weak points for ICS networks. As a result, ICSs are a valuable target for hackers searching for monetary gains or planning to cause destruction and chaos. Furthermore, recent attacks demonstrate a heightened understanding of ICS network configurations within hacking communities. A Defense-in-Depth strategy is the solution to these threats, applying multiple security layers to detect, interrupt, and prevent cyber threats before they cause damage. Our solution detects threats by deploying an Enhanced Data Historian for Detecting Cyberattacks. By introducing Machine Learning (ML), we enhance cyberattack detection by fusing network traffic and sensor data. Two computing models are examined: 1) a distributed computing model and 2) a localized computing model. The distributed computing model is powered by Apache Spark, introducing redundancy for detecting cyberattacks. In contrast, the localized computing model relies on a network traffic visualization methodology for efficiently detecting cyberattacks with a Convolutional Neural Network. These applications are effective in detecting cyberattacks with nearly 100% accuracy. Next, we prevent eavesdropping by applying Homomorphic Encryption for Secure Computing. HE cryptosystems are a unique family of public key algorithms that permit operations on encrypted data without revealing the underlying information. Through the Microsoft SEAL implementation of the CKKS algorithm, we explored the challenges of introducing Homomorphic Encryption to real-world applications. Despite these challenges, we implemented two ML models: 1) a Neural Network and 2) Principal Component Analysis. Finally, we hinder attackers by integrating a Cyberattack Lockdown Network with Secure Ultrasonic Communication. When a cyberattack is detected, communication for safety-critical elements is redirected through an ultrasonic communication channel, establishing physical network segmentation with compromised devices. We present proof-of-concept work in transmitting video via ultrasonic communication over an Aluminum Rectangular Bar. Within industrial environments, existing piping infrastructure presents an optimal solution for cost-effectively preventing eavesdropping. The effectiveness of these solutions is discussed within the scope of the nuclear industry.
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