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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Load altering attack-tolerant defense strategy for load frequency control system

Cyber attacks are emerging threats to every information-oriented energy management system. By violating the cyber systems, the hacker can disrupt the security and stability due to the strong coupling between the cyber and physical facilities. In this paper, one type of cyber attacks designated as the load altering attack is studied for the power system frequency control, and corresponding defense strategies are proposed to improve the frequency control performance. Considering the difficulty of the application of model-based controller into large-scale power systems, a novel model-free defense framework is for the first time presented. Under this framework, both active defense and passive defense strategies are designed. The former assumes that the defender has the initiative to learn different attack scenarios. Adaptive defense strategies are implemented using the online attack identification information and off-line trained strategy pool. The latter assumes that the defender passively tolerates various attack scenarios via the pre-trained off-line strategy. Both approaches prove to be effective through validation based on the IEEE benchmark systems. The proposed defense framework and defense strategies can be extended to other energy control systems to enhance their attack tolerance capability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The 2021 Defense Strategy Review and Modern Strategic Conflict (Workshop Summary)

On December 15-17, 2020, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “The 2021 Defense Strategy Review and Modern Strategic Conflict.” This session was the 7 th Annual Deterrence Workshop that CGSR organized, bringing together participants drawn across the policy, military, and technical communities of the United States and its allies. The workshop examined the challenges of regional wars and multi-domain competition and how a potential 2021 defense strategy review should address them. A special attention was paid to the question of escalation and how it can be controlled at various levels of conflict.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

The Cost and Benefit of Enhancing Cybersecurity for Hybrid AC/DC Grids

As critical interfaces of AC grids and DC grids inside a hybrid AC/DC grid, the voltage-sourced-converter (VSC) has been demonstrated to be vulnerable to false data injection (FDI) cyber-attacks. As a result, the cyber-attack-induced AC grid frequency deviations and DC grid voltage deviations threaten the secure operation. Here, to enhance cybersecurity in a not only feasible but also cost-effective manner, this paper proposes a cost-benefit-based cyber-defense strategy for a hybrid AC/DC grid. First, this paper establishes a spatial-temporal dual cyber-attack evaluation model, in which the cyber-attack-induced frequency and voltage deviations are modelled in both a spatially and temporally dual manner. Then, the proposed cost-benefit-based cyber-defense strategy is modelled as a VSC commitment problem to achieve the trade-off between maximizing the cyber-defense benefits and minimizing the cyber-defense costs. The VSC commitment problem is then mathematically convexified into a mixed-integer second-order cone programming (MISOCP) problem, which could be efficiently solved in an event-triggered manner against unfolding cyber-attack events. Simulation results on a test hybrid AC/DC grid verified the feasibility and the cost-effectiveness of the proposed cyber-defense strategy.

cost-benefit analysis↗
DOE OSTI2020

Space Strategy at a Crossroads: Opportunities and Challenges for 21st Century Competition

In its November 2018 report to Congress, the bipartisan National Defense Strategy Commission applauded the main themes of the Trump administration’s 2017 National Defense Strategy. But it was also deeply critical of the strategic thought so far done by the U.S. defense community about the requirements, operational and otherwise, of securing U.S. and allied interests in the types of conflicts we now face. Indeed, it assessed these shortfalls as crippling to the exercise of American power and as dangerous in crisis and war. Is the U.S. military space community exempt from such criticism? Should it be?

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Challenges in cybersecurity: Lessons from biological defense systems

Defending against novel, repeated, or unpredictable attacks, while avoiding attacks on the ‘self’, are the central problems of both mammalian immune systems and computer systems. Both systems have been studied in great detail, but with little exchange of information across the different disciplines. Here, we present a conceptual framework for structured comparisons across the fields of biological immunity and cybersecurity, by framing the context of defense, considering different (combinations of) defensive strategies, and evaluating defensive performance. Throughout this paper, we pose open questions for further exploration. In this work we hope to spark the interdisciplinary discovery of general principles of optimal defense, which can be understood and applied in biological immunity, cybersecurity, and other defensive realms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗
DOE OSTI2023

Plant physical defenses contribute to a latitudinal gradient in resistance to insect herbivory within a widespread perennial grass

Premise: Herbivore pressure can vary across the range of a species, resulting in different defensive strategies. If herbivory is greater at lower latitudes, plants may be better defended there, potentially driving a latitudinal gradient in defense. However, relationships that manifest across the entire range of a species may be confounded by differences within genetic subpopulations, which may obscure the drivers of these latitudinal gradients. Methods: We grew plants of the widespread perennial grass Panicum virgatum in a common garden that included genotypes from three genetic subpopulations spanning an 18.5° latitudinal gradient. We then assessed defensive strategies of these plants by measuring two physical resistance traits—leaf mass per area (LMA) and leaf ash, a proxy for silica—and multiple measures of herbivory by caterpillars of the generalist herbivore fall armyworm (Spodoptera frugiperda). Results: Across all genetic subpopulations, low-latitude plants experienced less herbivory than high-latitude plants. Within genetic subpopulations, however, this relationship was inconsistent—the most widely distributed and phenotypically variable subpopulation (Atlantic) exhibited more consistent latitudinal trends than either of the other two subpopulations. The two physical resistance traits, LMA and leaf ash, were both highly heritable and positively associated with resistance to different measures of herbivory across all subpopulations, indicating their importance in defense against herbivores. Again, however, these relationships were inconsistent within subpopulations. Conclusions: Defensive gradients that occur across the entire species range may not arise within localized subpopulations. Thus, identifying the drivers of latitudinal gradients in herbivory defense may depend on adequately sampling the diversity within a species.

09 BIOMASS FUELS↗
DOE OSTI2022

Cybersecurity Enhancement for Multi-Infeed High-Voltage DC Systems

Composed of multiple two-terminal high-voltage DC (HVDC) transmission systems, a multi-infeed HVDC (MIDC) system exchanges massive power among multiple asynchronous AC systems. However, as an intrinsically cyber-physical system, an MIDC system could suffer from cyber-attacks, leading to massive power mismatches in multiple AC systems, and resulting in catastrophic consequences. Since the sequential responses of an MIDC system and interconnected AC systems are in different timescales, this paper first establishes a two-timescale model to evaluate the sequential impacts caused by cyber-attacks. Then, an event-triggered cyber-defense strategy is proposed to enhance the cybersecurity of an MIDC system by mitigating multiple non-simultaneous cyber-attacks. Whenever new cyber-attack events occur, the proposed cyber-defense strategy, which is mathematically modeled as a mixed-integer quadratic programming problem, is executed on-line and updated in an event-triggered manner. Here, simulation results on an MIDC system demonstrate that the low-cost and almost blind cyber-attacks can cause severe frequency deviations, and the proposed strategy can mitigate multi-cyber-attacks effectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Machine Learning Based Resilience Testing of an Address Randomization Cyber Defense

Moving target defenses (MTDs) are widely used as an active defense strategy for thwarting cyberattacks on cyber-physical systems by increasing diversity of software and network paths. Recently, machine Learning (ML) and deep Learning (DL) models have been demonstrated to defeat some of the cyber defenses by learning attack detection patterns and defense strategies. It raises concerns about the susceptibility of MTD to ML and DL methods. Here, in this article, we analyze the effectiveness of ML and DL models when it comes to deciphering MTD methods and ultimately evade MTD-based protections in real-time systems. Specifically, we consider a MTD algorithm that periodically randomizes address assignments within the MIL-STD-1553 protocol—a military standard serial data bus. Two ML and DL-based tasks are performed on MIL-STD-1553 protocol to measure the effectiveness of the learning models in deciphering the MTD algorithm: 1) determining whether there is an address assignments change i.e., whether the given system employs a MTD protocol and if it does 2) predicting the future address assignments. The supervised learning models (random forest and k-nearest neighbors) effectively detected the address assignment changes and classified whether the given system is equipped with a specified MTD protocol. On the other hand, the unsupervised learning model (K-means) was significantly less effective. The DL model (long short-term memory) was able to predict the future addresses with varied effectiveness based on MTD algorithm's settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Understanding Structures of Cyber Competition in an Era of Major Power Rivalry

Over the past two decades, the cyber domain has emerged and evolved into a key strategic domain for nations across the globe. Security strategies are espoused by heads of state that focus on how to manage the increasingly enormous, crosscutting impact that the cyber domain has on national security across economic, military, intelligence, intellectual property, and countless other facets. These strategies frequently evolve, and even change entirely, as leaders adapt to new technologies and administrations change. Even if these strategies did not change at all, they would take inordinate amounts of time to effectively implement within the organizational structures of government. The time required to go from setting department and agency-level goals, to the time small teams have well-oiled processes and expertise to accomplish tactical objectives that meet the strategic vision is lengthy. With near certainty, by the time objectives and vision are implemented, the landscape, strategy, or both has changed entirely. While this churn will likely never cease due to the rapidly changing nature of the cyber domain, this problem raises an important question: can governmental structures be organized to rapidly adapt to changing cyber strategies? As offices responsible for particular missions in cyberspace shuffle about within the bureaucracy, are technical capabilities enabled or enhanced? No matter how advanced a particular technical capability is or how adept the staff is at solving problems, they will be ineffective if placed haphazardly within the organization: the right authorities may not exist for their office, the correct lines of interpersonal communication may not be established properly, or insufficient resources have not been allocated to effectively deploy a brilliant technical solution. This concept of organizational agility in the context of national cyber capabilities is important when taking into account the National Defense Strategy’s emphasis on cyber capability and the ability of the United States to compete and rapidly adapt to new challenges posed by rivals. As a nation, we are at a point where technology evolves rapidly enough to warrant thoughtful and nimble changes to the bureaucratic structures that support how cyber operations are carried out. Taking these questions and cross-comparing them to the organizational structures across China, Russia, and the United States provides for an interesting thought experiment. As non-democratic regimes, China and Russia have differing priorities and internal power dynamics than the United States and thus organize their governments differently. By combining known and broadcasted strategies of these nations with the observed technical capabilities demonstrated in the public domain, we can begin to see how organizational structures map to strategic goals and directly enable technical capabilities. Insight can be gained by introducing organizational structures into traditional analysis focusing solely around strategies and capabilities; additionally, otherwise unknown capabilities or intents might be discovered or inferred by analyzing organizational structures alone. Analyzing cyber operations from this oft-overlooked perspective could potentially provide useful insight and more concrete actions that can be undertaken to realize the National Defense Strategy’s goals.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Automated Adversary-in-the-Loop Cyber-Physical Defense Planning

Security of cyber-physical systems (CPS) continues to pose new challenges due to the tight integration and operational complexity of the cyber and physical components. To address these challenges, this article presents a domain-aware, optimization-based approach to determine an effective defense strategy for CPS in an automated fashion—by emulating a strategic adversary in the loop that exploits system vulnerabilities, interconnection of the CPS, and the dynamics of the physical components. Our approach builds on an adversarial decision-making model based on a Markov Decision Process (MDP) that determines the optimal cyber (discrete) and physical (continuous) attack actions over a CPS attack graph. The defense planning problem is modeled as a non-zero-sum game between the adversary and defender. We use a model-free reinforcement learning method to solve the adversary’s problem as a function of the defense strategy. We then employ Bayesian optimization (BO) to find an approximate best-response for the defender to harden the network against the resulting adversary policy. This process is iterated multiple times to improve the strategy for both players. We demonstrate the effectiveness of our approach on a ransomware-inspired graph with a smart building system as the physical process. Numerical studies show that our method converges to a Nash equilibrium for various defender-specific costs of network hardening.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An Analysis of Post Attack Impacts and Effects of Learning Parameters on Vulnerability Assessment of Power Grid

Due to the increasing number of heterogeneous devices connected to electric power grid, the attack surface increases the threat actors. Game theory and machine learning are being used to study the power system failures caused by external manipulation. Most of existing works in the literature focus on one-shot process of attacks and fail to show the dynamic evolution of the defense strategy. In this paper, we focus on an adversarial multistage sequential game between the adversaries of the smart electric power transmission and distribution system. We study the impact of exploration rate and convergence of the attack strategies (sequences of action that creates large scale blackout based on the system capacity) based on the reinforcement learning approach. We also illustrate how the learned attack actions disrupt the normal operation of the grid by creating transmission line outages, bus voltage violations, and generation loss. This simulation studies are conducted on IEEE 9 and 39 bus systems. The results show the improvement of the defense strategy through the learning process. The results also prove the feasibility of the learned attack actions by replicating the disturbances created in simulated power system.

attack impacts↗
DOE OSTI2024

Retrieval Augmented Generation for Robust Cyber Defense

In cybersecurity, the ability to efficiently analyze and respond to vulnerabilities, weaknesses, attack patterns, and threat tactics is critical for effective defense strategies. With the increasing complexity and volume of cybersecurity data, traditional methods of querying and retrieving information are often inadequate. To address this challenge, we implemented Retrieval-Augmented Generation (RAG) systems—CyRAG and GraphCyRAG—that integrate large language models (LLMs) with both structured data from relational databases and knowledge graphs such as Neo4j. CyRAG is designed to handle structured data, focusing on CVE (Common Vulnerabilities and Exposures) and CWE (Common Weakness Enumeration) entities to generate accurate and context-rich responses. In contrast, GraphCyRAG leverages Neo4j knowledge graphs to retrieve interconnected information from CVE, CWE, CAPEC (Common Attack Pattern Enumeration and Classification), and ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) datasets. By utilizing Neo4j’s graph-based framework, GraphCyRAG enables deeper traversal of relationships between vulnerabilities and attack patterns, providing cybersecurity analysts with more comprehensive insights into potential attack vectors and mitigation strategies. Our preliminary results demonstrate that integrating knowledge graphs with RAG significantly enhances both the accuracy and depth of threat analysis, allowing for the retrieval of dynamic, real-time data and the generation of contextually aware responses. This approach helps analysts uncover hidden relationships between cyber entities, predict exploit paths, and prioritize mitigation efforts effectively. The integration of RAG with cybersecurity knowledge graphs represents a significant advancement in cybersecurity threat intelligence, enabling more informed decision-making and stronger defense strategies.

97 MATHEMATICS AND COMPUTING↗