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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

WAMS-Based HVDC Damping Control for Cyber Attack Defense

Owing to the fast and large power regulating the capacity of the HVDC system, the wide-area measurement system (WAMS) based high voltage direct current (HVDC) system has been regarded as a prospective solution to deal with the low-frequency oscillation issue. However, due to the vulnerability of the WAMS communication, WAMS based HVDC system control can be a prime target of malicious penetrations that could lead to disastrous events. To remediate this adverse effect, an improved WAMS based HVDC damping control framework is proposed in this paper. First, a lightweight network named Attack Shuffle convolutional neural Networks (ASNet) is proposed to learn the characteristics of cyber attacks. Then, a model-free-based cyber attack defense framework is introduced to quickly identify the attack types based on the continuous wavelet transform and ASNet. Additionally, an improved control framework of the WAMS and HVDC-based wide-area power oscillation damping control (WH-PODC) is developed to provide different response control for mitigation of the impact of cyber attacks. Finally, the performance of the proposed WH-PODC control framework is evaluated with real PMU data in multiple scenarios in RTDS, where the results indicate that the response intensity can be kept under multiple types of cyber attacks while providing similar effectiveness in oscillation suppression to conventional controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Deep Reinforcement Learning for Distribution System Cyber Attack Defense with DERs

The use of smart inverter capabilities of distributed energy resources (DERs) enhances the grid reliability but in the meanwhile exhibits more vulnerabilities to cyber-attacks. This paper proposes a deep reinforcement learning (DRL)-based defense approach. The defense problem is reformulated as a Markov decision making process to control DERs and minimizing load shedding to address the voltage violations caused by cyber-attacks. The original soft actor-critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions for controlling DERs' setpoints and loadshedding scenarios. Numerical comparison results with other control approaches, such as Volt-VAR and Volt-Watt on the modified IEEE 33-node, show that the proposed method can achieve better voltage regulation and have less power losses in the presence of cyber-attacks.

active distribution systems↗
DOE OSTI2024

Engineering in Cyber Resilience with Cyber-Informed Engineering

Engineers have super powers to provide cybersecurity resilience with deterministic engineering solutions and to protect systems from the most catastrophic consequences that a cyber saboteur could cause. Come to this session to learn how to use engineering risk management skills to harden your engineered systems from cyberattacks. Objective 1 Identify what system functions could be digitally induced to cause undesired high-impact consequences. Objective 2 Analyze how loss or instability of digital controls in a subsystem could lead to high-impact consequences. Objective 3 Analyze how loss or instability in the digital connectivity between systems could lead to high-impact consequences. Objective 4 Identify engineering controls which could build resilience by eliminating digital loss or instability pathways or reduce the impact of digital loss or instability. This presentation will introduce Cyber-Informed Engineering, described below, and walk participants through specific engineering use cases to show how engineers can consider the potential for cyber sabotage in their existing system designs and enact deterministic engineering-based controls which eliminate pathways for attack or mitigate specific consequences. A wide variety of application use cases will be considered so that audience members can align the material with familiar engineering applications. CIE is an engineering approach that integrates cyber resilience into the conception, design, build, and operation of any physical system that has digital connectivity, sensors, monitoring, or control. CIE offers the opportunity to use engineering to eliminate or mitigate avenues for cyber attack—starting from the earliest stage of design and continuing throughout the system’s lifecycle. Today, engineers and industrial control system (ICS) technicians build engineered systems with specific goals for safety, reliability, and functionality. While systems engineering includes considerable safety and failure mode analysis, cybersecurity risks are often not specifically addressed—particularly the risks of intentional cyber compromise, exploitation, and misuse. Cyber-Informed Engineering pairs well with traditional cyber defenses and offers an extra designed-in protection to eliminate the most catastrophic consequences which can be realized by an adversary should traditional cyber defenses fail.

42 ENGINEERING↗
DOE OSTI2023

Complete Evaluation on Advanced Reactor Machine Learning Subversion Attacks (Final)

Navigating through the world of Artificial Intelligence (AI) in nuclear reactors and their Instrumentation and Control (I&C) systems demands a careful, deliberate journey. AI’s capability to manage massive datasets and streamline control systems has indeed carved out a significant role in various sectors, including nuclear energy. However, while AI, and particularly Large Language Models (LLMs), bring a lot to the table in terms of operational efficiency and anomaly detection, they also expose the sector to a new breed of cybersecurity threats, like Inference Attacks, Adversarial Attacks, and Trojan Attacks. This guide is designed to be a straightforward manual, diving deep into the intertwining worlds of AI and cybersecurity within nuclear reactors, and tailoring insights for three crucial audiences: I&C Vendors/Developers, Nuclear Regulators, and Nuclear Reactor Operators and Cyber Defense Teams. (1) Section 2, directed at I&C Vendors/Developers, will provide a clear and focused look at several cybersecurity attacks, offering practical recommendations and detailed scenarios related to AI cybersecurity. This section isn’t just about identifying problems but also about giving solid, usable solutions. (2) Section 3, meant for Nuclear Regulators, gets straight to the point about regulations, policy suggestions, and guidelines that are needed to lay down a robust, secure, and ethical foundation for the application of AI in nuclear operations. The focus is on making sure that everything adheres to international standards and laws while being practicable and clear-cut. (3) Section 4, aimed at Nuclear Reactor Operators and Cyber Defense Teams, offers an exhaustive exploration and technical reports, with clear recommendations and scenario analyses vital to protect operational environments and guarantee the secure application of AI in nuclear reactor operations. The goal is simple: as we step into an era where AI becomes a fundamental element of our technological and energy infrastructures, this guide is here to act as a clear, direct handbook, ensuring that AI is implemented within the nuclear sector in a manner that is secure, responsible, and practical. It’s about striking a balance – optimizing the undeniable benefits offered by AI while securing and shielding against potential cyber threats as we move through this new and complex landscape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Design and Implementation of Full-Scale Industrial Control System Test Bed for Assessing Cyber-Security Defenses

In response to the increasing awareness of the Ethernet-based threat surface of industrial control systems (ICS), both the research and commercial communities are responding with ICS-specific security solutions. Unfortunately, many of the properties of ICS environments that contribute to the extent of this threat surface (e.g. age of devices, inability or unwillingness to patch, criticality of the system) similarly prevent the proper testing and evaluation of these security solutions. Production environments are often too fragile to introduce unvetted technology and most organizations lack test environments that are sufficiently consistent with production to yield actionable results. Cost and space requirements prevent the creation of mirrored physical environments leading many to look towards simulation or virtualization. Examples in literature provide various approaches to building ICS test beds, though most of these suffer from a lack of realism due to contrived scenarios, synthetic data and other compromises. In this paper, we provide a design methodology for building highly realistic ICS test beds for validating cybersecurity defenses. We then apply that methodology to the design and building of a specific test bed and describe the results and experimental use cases.

Gillen, Rob↗
DOE OSTI2021

Neighborhood Keeper

Neighborhood Keeper is a collective defense and community-wide visibility solution that provides a more effective industrial cyber defense by sharing threat intelligence at machine-speed across industries and geographic regions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

D2U: Data Driven User Emulation for the Enhancement of Cyber Testing, Training, and Data Set Generation

Whether testing intrusion detection systems, conducting training exercises, or creating data sets to be used by the broader cybersecurity community, realistic user behavior is a critical component of a cyber range. Existing methods either rely on network level data or replay recorded user actions to approximate real users in a network. Our work is the first to produce generative models trained on actual user data (sequences of application usage) collected on endpoints. Once trained to the user's behavioral data, these models can generate novel sequences of actions %that appear to come from the same distribution as the training data. These sequences of actions are then fed to our custom software via configuration files, which replicate those behaviors on end devices. Notably, our models are platform agnostic and could generate behavior data for any emulation software package. In this paper we present our model generation process, software architecture, and an initial evaluation of the fidelity of our models. Our software is currently deployed in a cyber range to help evaluate the efficacy of defensive cyber technologies. We suggest additional ways that the cyber community as a whole can benefit from more realistic user behavior emulation. The data used to train our model, as well as sample configuration files produced by the model, are available at [redacted].

Oesch, T↗
DOE OSTI2023

Collaboration and Negotiation

Collaboration and Negotiation is a critical high-level function of an Autonomous Intelligent Cyber-Defense Agent (AICA) that enables communication among agents, central cyber C2, and human operators. Maintaining the Confidentiality, Integrity, and Availability (CIA) triad while achieving mission goals requires stealthy AICA agents to exercise: 1) minimal communication as needed for avoiding detection, 2) verification of information received with possibly limited resources, and 3) active learning during operations to address dynamic conditions. Moreover, negotiations to jointly identify and execute a Course of Action (COA) solution will require building consensus under distributed and/or decentralized multiagent settings with information uncertainties. This chapter presents algorithmic approaches for enabling the collaboration and negotiation function. Strengths and limitations of potential techniques are identified, and a representative example is illustrated. Recommendations for future development are also discussed.

Chatterjee, Samrat↗
DOE OSTI2024

ARCADE (Advanced Reactor Cyber Analysis and Development Environment)

SAND2025-11780O ARCADE (Advanced Reactor Cyber Analysis and Development Environment) software performs cybersecurity experiments on Defensive Cyber Security Architectures (DCSA) for Distributed Control Systems (DCSs). The application is integrated into a cohesive environment that performs cyber risk analyses and reduces costs. ARCADE can investigate the entire cyber-attack surface of a DCS from the physics of control, down to the firmware of individual components with automated efficiency. ARCADE has five major functional components: the Data Broker system, the virtualization environment, the cyber-attack simulator, the cyber-physical analysis system, and the physics simulator. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Valme, Romuald↗
DOE OSTI2022

A Cryptographic Method for Defense Against MiTM Cyber Attack in the Electricity Grid Supply Chain

Critical infrastructures such as the electricity grid can be severely impacted by cyber-attacks on its supply chain. Hence, having a robust cybersecurity infrastructure and management system for the electricity grid is a high priority. This paper proposes a cyber-security protocol for defense against man-in-the-middle (MiTM) attacks to the supply chain, which uses encryption and cryptographic multi-party authentication. A cyber-physical simulator is utilized to simulate the power system, control system, and security layers. The correctness of the attack modeling and the cryptographic security protocol against this MiTM attack is demonstrated in four different attack scenarios.

Paul, Shuva↗
DOE OSTI2023

A Real-Time ANPC Inverter Digital Twin with Integrated Design-For-Trust

The demand for renewable energy has increased over the last few years, and so has the demand for greater expectations within the energy market. This increasing trend has been accompanied by more significant usage of internet-connected devices (IoT), leading to critical electrical infrastructure being connected to the internet. Implementing internet connectivity with such devices and systems provides benefits such as improving the system's performance, facilitating irregularity and anomaly mitigation, and providing additional situational awareness for enhanced decision-making. However, enhancing the connected system with IoT introduces a drawback – a greater vulnerability to cyber-attacks. Cyber-attacks targeting critical infrastructure in the electrical sector have occurred in the United States and Ukraine. These cyber-attacks highlight and expose vulnerabilities that a system inherits when connecting to the internet. These attacks left thousands of customers without electricity for hours until operators could regain control of the electric utility grid. Therefore, to address the vulnerabilities of an internet-connected power electronic device, this work focused on the hardware layer of the system. Implementing a cyber-control system inside the hardware layer can significantly reduce the possibility of an attacker patching malicious controller firmware into a photovoltaic grid-connected inverter, thus mitigating the likelihood that the inverter becomes inactive a cyber-attack scenario. With this mitigation technique, if a cyberattack is successful and an attacker gains control of the network, a cyber-defense technique is in place to mitigate the impact of the cyber-attack. This additional protection layer was developed based on an innovative concept known as Digital Twin (DT). A DT, in this case, replicates an Active-Neutral Point Clamped (ANPC) inverter and was designed using a hardware language known as VHDL (Very High-Speed Integrated Circuit Hardware Description Language) and applied to Field-Programmable-GateArray (FPGA). The DT is embedded within the FPGA and contained in a controller board, the UCB (Unified Controller Board), developed by the University of Arkansas electrical engineering team. This UCB also contains two Digital Signal Processors (DSPs) responsible for generating associated signals to control an authentic physical inverter. These DSP signals are received and processed by the FPGA that implements the DT of an ANPC; in other words, it simulates in realtime the expected output of an actual ANPC inverter using the signals from the DSP. When a new firmware is ready to be patched, the DT provides output signals simulating behavior that a real ANPC inverter would generate with the new firmware. The new firmware is tested to check if it meets all the operational requirements established using a Design-For-Trust technique (DFTr). If the new firmware fails in at least one of the DFT tests, it is considered malicious and must be rejected. This work is divided into sections, such as Background, which explains the pieces that were used and the strategy behind this work; Process and Procedure, which explains the methodology that was adopted to prove the reliability and effectiveness of this work; Results and Discussion, where the simulations and results are described and explained; followed by Conclusion and Future work section, which concludes this work and adds possible future projects to continue this work further.

do Amaral Custodio, Paulo Vitor↗
DOE OSTI2021

Design Considerations for Distributed Energy Resource Honeypots and Canaries

There are now over 2.5 million Distributed Energy Resource (DER) installations connected to the U.S. power system. These installations represent a major portion of American electricity critical infrastructure and a cyberattack on these assets in aggregate would significantly affect grid operations. Virtualized Operational Technology (OT) equipment has been shown to provide practitioners with situational awareness and better understanding of adversary tactics, techniques, and procedures (TTPs). Deploying synthetic DER devices as honeypots and canaries would open new avenues of operational defense, threat intelligence gathering, and empower DER owners and operators with new cyber-defense mechanisms against the growing intensity and sophistication of cyberattacks on OT systems. Well-designed DER canary field deployments would deceive adversaries and provide early-warning notifications of adversary presence and malicious activities on OT networks. In this report, we present progress to design a high-fidelity DER honeypot/canary prototype in a late-start Laboratory Directed Research and Development (LDRD) project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

BioSecure Digital Twin: Manufacturing Innovation and Cybersecurity Resilience

U.S. national security, prosperity, economy, and well-being require secure, flexible, and resilient Biopharmaceutical Manufacturing. The COVID-19 pandemic reaffirmed that the biomedical production value-chain is vulnerable to disruption and has been under attack from sophisticated nation-state adversaries. Current cyber defenses are inadequate, and the integrity of critical production systems and processes are inherently vulnerable to cyber-attacks, human error, and supply chain disruptions. The following chapter explores how a BioSecure Digital Twin will improve U.S. manufacturing resilience and preparedness to respond to these hazards by significantly improving monitoring, integrity, security, and agility of our manufacturing infrastructure and systems. The BioSecure Digital Twin combines a scalable manufacturing framework with a robust platform for monitoring and control to increase U.S. biopharma manufacturing resilience. Then, the chapter discusses some of the inherent vulnerabilities and challenges at the nexus of health and advanced manufacturing. Next, the chapter highlights that as the Pandemic evolves, we need agility and resilience to overcome significant obstacles. This section highlights an innovative application of Cyber Informed Engineering to developing and deploying a BioSecure Digital Twin to improve the resilience and security of the biopharma industrial supply chain and production processes. Finally, the chapter concludes with a process framework to complement the Digital Twin platform, called the Biopharma (Observe, Orient, Decide, Act) OODA Loop Framework (BOLF), a four-step approach to decision-making outputs from the Digital Twin. The BOLF will help end users leverage twin technology by distilling the available information, focusing the data on context, and rapidly making the best decision while remaining cognizant of changes that can be made as more data becomes available.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Intern Poster: AIBOMs in Automated Defense: Capabilities & Challenges

AI is increasingly used in critical infrastructure, but it's often a “black box” that is difficult to understand. AIBOMs, or AI Bill of Materials, are one way to increase AI transparency and accountability. They can also be used in automated cyber defense. AIBOMs are a new concept with challenges to widespread adoption, but their potential in cybersecurity makes them a worthwhile investment.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Cyber-Enabled Sabotage, Critical Function Assurance, and Cyber-Informed Engineering

Cyber-enabled Sabotage, Critical Function Assurance, and Cyber-Informed Engineering: This discussion will introduce the idea of cyber-enabled sabotage, and the role engineering plays in the cyber defense of critical functions with a focus on electric power systems. It will outline how and why engineering practice must be used to apply cybersecurity principles to establish safe and reliable operations even in the face of determined and skilled adversaries, and give an overview of INL’s Consequence-Driven Cyber-Informed Engineering methodology to apply these principles. There will be an opportunity for audience questions and answers at the end of the session.

42 ENGINEERING↗
DOE OSTI2023

AI-based Detection and Defense Against Cyberattacks in Distributed Energy Resources

This study will provide comprehensive artificial intelligence (AI)-based solution tools for network security, malware prevention, and sensor data anomaly detection for distributed energy resource (DER) research, development, and demonstration. DER technologies are energy systems (e.g., solar panels, wind turbines, and energy storage systems) that are often connected to the internet and thus vulnerable to cyberattacks. Cybersecurity should be of primary concern for DERs, which is why we propose an integrated multi-layer cyber-defense system for DERs. This system encompasses risk assessments, network security, malware prevention, and detection of anomalies in the sensor data. Implementation of a comprehensive risk assessment with an overview of the model architecture should be the primary step, and should include the potential impact of experiencing, at a given time, one or more cyberattacks on the system. The second step is to ensure that the network security includes firewalls, intrusion detection, and malware prevention. The third step is to provide solution tools that enable sensor data anomaly detection for DERs. By incorporating these considerations into DER research, development, and demonstration, organizations can help ensure the safety and security of their systems and protect against potential cyberattacks.

20 FOSSIL-FUELED POWER PLANTS↗