Cybersecurity Challenges of Power Transformers

The rise of cyber threats on critical infrastructure and its potential for devastating consequences, has significantly increased. The dependency of new power grid technology on information, data analytic and communication systems make the entire electricity network vulnerable to cyber threats. Power transformers play a critical role within the power grid and are now commonly enhanced through factory add-ons or intelligent monitoring systems added later to improve the condition monitoring of critical and long lead time assets such as transformers. However, the increased connectivity of those power transformers opens the door to more cyber attacks. Therefore, the need to detect and prevent cyber threats is becoming critical. The first step towards that would be a deeper understanding of the potential cyber-attacks landscape against power transformers. Much of the existing literature pays attention to smart equipment within electricity distribution networks, and most methods proposed are based on model-based detection algorithms. Moreover, only a few of these works address the security vulnerabilities of power elements, especially transformers within the transmission network. To the best of our knowledge, there is no study in the literature that systematically investigate the cybersecurity challenges against the newly emerged smart transformers. This paper addresses this shortcoming by exploring the vulnerabilities and the attack vectors of power transformers within electricity networks, the possible attack scenarios and the risks associated with these attacks.Comment: 11 page

Data-Driven Stealthy Injection Attacks on Smart Grid

Smart grid cyber-security has come to the forefront of national security priorities due to emergence of new cyber threats such as the False Data Injection (FDI) attack. Using FDI, an attacker can intelligently modify smart grid measurement data to produce wrong system states which can directly affect the safe operation of the physical grid. The goal of this thesis is to investigate key research problems leading to the discovery of significant vulnerabilities and their impact on smart grid operation. The first problem investigates how a stealthy FDI attack can be constructed without the knowledge of system parameters, e.g., line reactance, bus and line connectivity. We show how an attacker can successfully carry out an FDI attack by analysing subspace information of the measurement data without requiring the system topological knowledge. In addition, we make a critical observation that existing subspace based attacks would fail in the presence of gross errors and missing values in the observed data. Next, we show how an attacker can circumvent this problem by using a sparse matrix separation technique. Extensive evaluation on several benchmark systems demonstrates the effectiveness of this approach. The second problem addresses the scenario when an attacker may eavesdrop but only has access to a limited number of measurement devices to inject false data. We show how an attack can be constructed by first estimating the hidden system topology from measurement data only and then use it to identify a set of critical sensors for data injection. Extensive experiments using graph-theoretic and eigenvalue analyses demonstrate that the estimated power grid structure is very close to the original grid topology, and a stealthy FDI attack can be carried out using only a small fraction of all available sensors. The third problem investigates a new type of stealthy Load Redistribution (LR) attack using FDI which can deliberately cause changes in the Locational Marginal Price (LMP) of smart grid nodes. To construct the LR-FDI attack, the Shift factor is estimated from measurement and LMP data. Finally, the impact of the attacks on the state estimation and the nodal energy prices is thoroughly investigated

Bridging Machine Learning for Smart Grid Applications

This dissertation proposes to develop, leverage, and apply machine learning algorithms on various smart grid applications including state estimation, false data injection attack detection, and reliability evaluation. The dissertation is divided into four parts as follows.. Part I: Power system state estimation (PSSE). The PSSE is commonly formulated as a weighted least-square (WLS) algorithm and solved using iterative methods such as Gauss-Newton methods. However, iterative methods have become more sensitive to system operating conditions than ever before due to the deployment of intermittent renewable energy sources, zero-emission technologies (e.g., electric vehicles), and demand response programs. Efficient approaches for PSSE are required to avoid pitfalls of the WLS-based PSSE computations for accurate prediction of operating conditions. The first part of this dissertation develops a data-driven real-time PSSE using a deep ensemble learning algorithm. In the proposed approach, the ensemble learning setup is formulated with dense residual neural networks as base-learners and a multivariate-linear regressor as a meta-learner. Historical measurements and states are utilized to train and test the model. The trained model can be used in real-time to estimate power system states (voltage magnitudes and phase angles) using real-time measurements. Most of current data-driven PSSE methods assume the availability of a complete set of measurements, which may not be the case in real power system data acquisition. This work adopts multivariate linear regression to forecast system states for instants of missing measurements to assist the proposed PSSE technique. Case studies are performed on various IEEE standard benchmark systems to validate the proposed approach. Part II: Cyber-attacks on Voltage Regulation. Several wired and wireless advanced communication technologies have been used for coordinated voltage regulation schemes in distribution systems. These technologies have been employed to both receive voltage measurements from field sensors and transmit control settings to voltage regulating devices (VRDs). Communication networks for voltage regulation can be susceptible to data falsification attacks, which can lead to voltage instability. In this context, an attacker can alter multiple field measurements in a coordinated manner to disturb voltage control algorithms. The second part of this dissertation develops a machine learning-based two-stage approach to detect, locate, and distinguish coordinated data falsification attacks on control systems of coordinated voltage regulation schemes in distribution systems with distributed generators. In the first stage (regression), historical voltage measurements along with current meteorological data (solar irradiance and ambient temperature) are provided to random forest regressor to forecast voltage magnitudes of a given current state. In the second stage, a logistic regression compares the forecasted voltage with the measured voltage (used to set VRDs) to detect, locate, and distinguish coordinated data falsification attacks in real-time. The proposed approach is validated through several case studies on a 240-node real distribution system (based in the USA) and the standard IEEE 123-node benchmark distribution system.Part III: Cyber-attacks on Distributed Generators. Part III of the dissertation proposes a deep learning-based multi-label classification approach to detect coordinated and simultaneously launched data falsification attacks on a large number of distributed generators (DGs). The proposed approach is developed to detect power output manipulation and falsification attacks on DGs including additive attacks, deductive attacks, and combination of additive and deductive attacks (attackers use the combination of additive and deductive attacks to camouflage their attacks). The proposed approach is demonstrated on several systems including the 240-node and IEEE 123-node distribution test system. Part IV: Composite System Reliability Evaluation. Traditional composite system reliability evaluation is computationally demanding and may become inapplicable to large integrated power grids due to the requirements of repetitively solving optimal power flow (OPF) for a large number of system states. Machine learning-based approaches have been used to avoid solving OPF in composite system reliability evaluation except in the training stage. However, current approaches have been utilized only to classify system states into success and failure states (i.e., up or down). In other words, they can be used to evaluate power system probability and frequency reliability indices, but they cannot be used to evaluate power and energy reliability indices unless OPF is solved for each failure state to determine minimum load curtailments. In the fourth part of this dissertation, a convolutional neural network (CNN)-based regression approach is proposed to determine the minimum amount of load curtailments of sampled states without solving OPF. Unavoidable load curtailments due to failures are then used to evaluate power and energy indices (e.g., expected demand not supplied) as well as to evaluate the probability and frequency indices. The proposed approach is applied on several systems including the IEEE Reliability Test System and Saskatchewan Power Corporation in Canada

Space Systems: Emerging Technologies and Operations

SPACE SYSTEMS: EMERGING TECHNOLOGIES AND OPERATIONS is our seventh textbook in a series covering the world of UASs / CUAS/ UUVs. Other textbooks in our series are Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA\u27s Advanced Air Assets, 1st edition. Our previous six titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols et al., 2021) (Nichols R. K. et al., 2020) (Nichols R. et al., 2020) (Nichols R. et al., 2019) (Nichols R. K., 2018) Our seventh title takes on a new purview of Space. Let\u27s think of Space as divided into four regions. These are Planets, solar systems, the great dark void (which fall into the purview of astronomers and astrophysics), and the Dreamer Region. The earth, from a measurement standpoint, is the baseline of Space. It is the purview of geographers, engineers, scientists, politicians, and romantics. Flying high above the earth are Satellites. Military and commercial organizations govern their purview. The lowest altitude at which air resistance is low enough to permit a single complete, unpowered orbit is approximately 80 miles (125 km) above the earth\u27s surface. Normal Low Earth Orbit (LEO) satellite launches range between 99 miles (160 km) to 155 miles (250 km). Satellites in higher orbits experience less drag and can remain in Space longer in service. Geosynchronous orbit is around 22,000 miles (35,000 km). However, orbits can be even higher. UASs (Drones) have a maximum altitude of about 33,000 ft (10 km) because rotating rotors become physically limiting. (Nichols R. et al., 2019) Recreational drones fly at or below 400 ft in controlled airspace (Class B, C, D, E) and are permitted with prior authorization by using a LAANC or DroneZone. Recreational drones are permitted to fly at or below 400 ft in Class G (uncontrolled) airspace. (FAA, 2022) However, between 400 ft and 33,000 ft is in the purview of DREAMERS. In the DREAMERS region, Space has its most interesting technological emergence. We see emerging technologies and operations that may have profound effects on humanity. This is the mission our book addresses. We look at the Dreamer Region from three perspectives:1) a Military view where intelligence, jamming, spoofing, advanced materials, and hypersonics are in play; 2) the Operational Dreamer Region; whichincludes Space-based platform vulnerabilities, trash, disaster recovery management, A.I., manufacturing, and extended reality; and 3) the Humanitarian Use of Space technologies; which includes precision agriculture wildlife tracking, fire risk zone identification, and improving the global food supply and cattle management. Here’s our book’s breakdown: SECTION 1 C4ISR and Emerging Space Technologies. C4ISR stands for Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance. Four chapters address the military: Current State of Space Operations; Satellite Killers and Hypersonic Drones; Space Electronic Warfare, Jamming, Spoofing, and ECD; and the challenges of Manufacturing in Space. SECTION 2: Space Challenges and Operations covers in five chapters a wide purview of challenges that result from operations in Space, such as Exploration of Key Infrastructure Vulnerabilities from Space-Based Platforms; Trash Collection and Tracking in Space; Leveraging Space for Disaster Risk Reduction and Management; Bio-threats to Agriculture and Solutions From Space; and rounding out the lineup is a chapter on Modelling, Simulation, and Extended Reality. SECTION 3: Humanitarian Use of Space Technologies is our DREAMERS section. It introduces effective use of Drones and Precision Agriculture; and Civilian Use of Space for Environmental, Wildlife Tracking, and Fire Risk Zone Identification. SECTION 3 is our Hope for Humanity and Positive Global Change. Just think if the technologies we discuss, when put into responsible hands, could increase food production by 1-2%. How many more millions of families could have food on their tables? State-of-the-Art research by a team of fifteen SMEs is incorporated into our book. We trust you will enjoy reading it as much as we have in its writing. There is hope for the future.https://newprairiepress.org/ebooks/1047/thumbnail.jp

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

The U.S. Army in the Iraq War – Volume 1: Invasion – Insurgency – Civil War, 2003-2006

The Iraq War has been the costliest U.S. conflict since the Vietnam War. To date, few official studies have been conducted to review what happened, why it happened, and what lessons should be drawn. The U.S. Army in the Iraq War is the Army\u27s initial operational level analysis of this conflict, written in narrative format, with assessments and lessons embedded throughout the work. This study reviews the conflict from a Landpower perspective and includes the contributions of coalition allies, the U.S. Marine Corps, and special operations forces. Presented principally from the point of view of the commanders in Baghdad, the narrative examines the interaction of the operational and strategic levels, as well as the creation of theater level strategy and its implementation at the tactical level. Volume 1 begins in the truce tent at Safwan Airfield in southern Iraq at the end of Operation DESERT STORM and briefly examines actions by U.S. and Iraqi forces during the interwar years. The narrative continues by examining the road to war, the initially successful invasion, and the rise of Iraqi insurgent groups before exploring the country\u27s slide toward civil war. This volume concludes with a review of the decision by the George W. Bush administration to “surge” additional forces to Iraq, placing the conduct of the “surge” and its aftermath in the second volume. This study was constructed over a span of 4 years and relied on nearly 30,000 pages of handpicked declassified documents, hundreds of hours of original interviews, and thousands of hours of previously unavailable interviews. Original interviews conducted by the team included President George W. Bush, Secretary of State Condoleezza Rice, Secretaries of Defense Leon Panetta and Robert Gates, Chairmen of the Joint Chiefs of Staff, and every theater commander for the war, among many others. With its release, this publication, The U.S. Army in the Iraq War, represents the U.S. Government\u27s longest and most detailed study of the Iraq conflict thus far.https://digitalcommons.usmalibrary.org/books/1018/thumbnail.jp

The U.S. Army in the Iraq War – Volume 1: Invasion – Insurgency – Civil War, 2003-2006

The Iraq War has been the costliest U.S. conflict since the Vietnam War. To date, few official studies have been conducted to review what happened, why it happened, and what lessons should be drawn. The U.S. Army in the Iraq War is the Army’s initial operational level analysis of this conflict, written in narrative format, with assessments and lessons embedded throughout the work. This study reviews the conflict from a Landpower perspective and includes the contributions of coalition allies, the U.S. Marine Corps, and special operations forces. Presented principally from the point of view of the commanders in Baghdad, the narrative examines the interaction of the operational and strategic levels, as well as the creation of theater level strategy and its implementation at the tactical level. Volume 1 begins in the truce tent at Safwan Airfield in southern Iraq at the end of Operation DESERT STORM and briefly examines actions by U.S. and Iraqi forces during the interwar years. The narrative continues by examining the road to war, the initially successful invasion, and the rise of Iraqi insurgent groups before exploring the country’s slide toward civil war. This volume concludes with a review of the decision by the George W. Bush administration to “surge” additional forces to Iraq, placing the conduct of the “surge” and its aftermath in the second volume. This study was constructed over a span of 4 years and relied on nearly 30,000 pages of hand-picked declassified documents, hundreds of hours of original interviews, and thousands of hours of previously unavailable interviews. Original interviews conducted by the team included President George W. Bush, Secretary of State Condoleezza Rice, Secretaries of Defense Leon Panetta and Robert Gates, Chairmen of the Joint Chiefs of Staff, and every theater commander for the war, among many others. With its release, this publication, The U.S. Army in the Iraq War, represents the U.S. Government’s longest and most detailed study of the Iraq conflict thus far. NOTICE: Due to the high cost of printing, only a limited numbers of hard copies of The U.S. Army in the Iraq War will be produced. These copies will be distributed primarily to military educational institutions across the Joint force. Hardcopies of the study can be acquired through the Government Printing Office Bookstore. Organizations and individuals will be able to order printed copies. Both volumes of The U.S. Army in the Iraq War are available for pre-order through the GPO Bookstore. Volume 1 can be found here. And Volume 2 can be found here. ADDENDUM: The U.S. Army Heritage and Education Center (USAHEC) has no archive of declassified documents except for the declassified documents from U.S. Central Command (USCENTCOM) posted online here. USAHEC does not have the authority to declassify or to review OIF sources for release.https://press.armywarcollege.edu/monographs/1385/thumbnail.jp