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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ARCADE Analysis Methods & Validation Pathway

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) provides an automated analysis system which supports risk-informed performance based (RIPB) evaluations of nuclear control systems. Every possible cyber threat which could lead to consequence is identified by simulating the unsafe control action sequences which transform digital harm into physical harm. Eliminating the simulation of complex digital cyber attack chains cuts out unnecessary computational overhead and focuses directly on the physics of cyber-physical attacks. This focus enables designers to make informed decisions which can entirely eliminate categories of cyber threats against advanced reactors through the physical nature of the plant design. This narrowing of cyber threat against nuclear power plants through the physics of the system is intended to make any remaining threat management and cost efficient. This is the goal of the Tiered Cyber Analysis (TCA) outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors. ARCADE has been custom developed to meet the demands of the rigorous analysis required in Tier 1 of the TCA, which forms the foundation of the TCA process. Currently, ARCADE is still under development, but has made significant leaps in capability. A pilot analysis on the opensource Asherah simulator was performed which demonstrated key functionality goals. The next stage of ARCADE development involves improvements to the applications which support the analysis system, and enabling the analysis system to utilize the full suite of unsafe control action simulations. Since the analysis method’s core functions are complete, validation of the analysis method will be started concurrent to the next development stages. The automated analysis ARCADE will provide can radically change the cybersecurity design process for advanced reactors, reducing the cost of security implementation while enhancing cyber resilience. The pathway for ARCADE’s development to this goal has become much clearer. The majority of technical hurdles have been cleared, and the remaining development needs have been solidified. ARCADE is now capable of assisting the advanced reactor design process and directly support advanced reactor industry RIPB practices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Electricity Subsector Transmission Resilience Maturity Model (TRMM) User Guide

The electric transmission sector is facing a range of threats to its functionality that are either new, more severe than experienced in earlier years, or more well understood. Such threats include more frequent and more severe extreme weather events, wildfires, droughts, and human-caused physical and cyberattacks. They also include geological, electromagnetic, and biological events. The novelty or increasing severity of these threats creates a significant need for transmission owners to implement programs to prevent, prepare for, respond to, and recover from such incidents. The national and economic security of the United States depends on the reliable functioning of the Nation’s critical infrastructure in the face of such threats, and the transmission networks are essential components of that infrastructure. The Electricity Subsector Transmission Resilience Maturity Model (TRMM) is a tool that a transmission organization can use to objectively evaluate and benchmark its currently established transmission resilience strategies, programs, policies, and investments, in order to target and prioritize enhancements where needed. The TRMM was developed to address the unique characteristics of the transmission system. The model can enable users to: • evaluate and benchmark their organization’s resilience capabilities, effectively and consistently • prioritize actions and investments to improve the resilience of their systems • share transmission-related knowledge, best practices, and relevant references within their organization and with business partners as a means to improve resilience capabilities • contribute to increasing the overall resilience of the Nation’s transmission systems. The TRMM provides descriptive rather than prescriptive industry-focused guidance. The model content is presented at a high level of abstraction so that it can be interpreted by transmission organizations of various types, structures, and sizes. The model is designed to an be easy-to-use, self-assessment tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

On the vulnerability of data-driven structural health monitoring models to adversarial attack

Many approaches at the forefront of structural health monitoring rely on cutting-edge techniques from the field of machine learning. Recently, much interest has been directed towards the study of so-called adversarial examples; deliberate input perturbations that deceive machine learning models while remaining semantically identical. This article demonstrates that data-driven approaches to structural health monitoring are vulnerable to attacks of this kind. In the perfect information or ‘white-box’ scenario, a transformation is found that maps every example in the Los Alamos National Laboratory three-storey structure dataset to an adversarial example. Also presented is an adversarial threat model specific to structural health monitoring. The threat model is proposed with a view to motivate discussion into ways in which structural health monitoring approaches might be made more robust to the threat of adversarial attack.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Domestic Extremism (Executive Summary)

Domestic extremism (DE) has been a growing concern in the U.S. in recent months, as illustrated in multiple bulletins from the Department of Homeland Security (DHS) warning law enforcement partners of the heightened threat. As concerns about these actors grows, it is important that facilities in the U.S. and internationally that protect critical assets, such as sensitive information, hazardous materials, or critical infrastructure, have effective methods in place to secure those assets. DE has challenged security systems through the danger of insider attack and violence, creating a new threat to be countered. In this effort, therefore, we used a literature review and focus group discussions with experts in critical asset security and extremism to understand the nature of the domestic extremist threat, to identify best practices in securing assets, recognize potential gaps in security measures to be corrected, and recommend actions for the Office of Radiological Security (ORS) to address DE with its partners.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Distribution, Ecology, Life History, and Conservation Status of the Berry Cave Salamander (Gyrinophilus gulolineatus)

The Berry Cave Salamander (Gyrinophilus gulolineatus) is a neotenic, stygobitic salamander endemic to eight cave systems and an isolated surface record in the Appalachian Valley and Ridge of eastern Tennessee. We conducted surveys for G. gulolineatus from 2017–2019 to assess the status of the species, locate new populations, and address knowledge gaps related to life history and population ecology required for conservation assessment. We confirmed G. gulolineatus presence at four historical sites, but we did not observe the species at any additional caves. At the three known sites with greatest abundance, visual counts per survey ranged 0–19 salamanders in 2017–2019. There was no apparent trend in abundance at Berry Cave. Visual counts declined 65% since the mid-2000s at Meads Quarry Cave and 80% since the early 1980s at Mudflats Cave. Mark-recapture studies in 160-m of cave stream at Berry Cave in 2017–2018 and 900-m of cave stream at Meads Quarry Cave in 2008 yielded population size estimates that ranged from 34–78 and 15–65 individuals, respectively. We identified 13 existing or potential threats to populations. Habitat degradation and groundwater contamination (associated with urbanization of the Knoxville metropolitan area and past mining operations) represent the most evident threats to long-term viability. Based on our conservation assessments, we recommend a rank of Endangered under IUCN Red List criteria and Critically Imperiled–Imperiled (G1G2) under NatureServe criteria. In opposition to the recent U.S. Fish & Wildlife Service decision, we advocate that, at minimum, G. gulolineatus remain a Candidate Species. Given the identified threats and these ranks, we offer several recommendations for research, conservation, and management of this rare salamander.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Addressing Consequence within Operational Risk (O.T. Gagnon III) 9-18-2024

Addressing Consequence within Operational Risk: Why threats and security are just not that important! When dealing with cyber or physical risk within any critical infrastructure (CI) environment, don’t concern yourself with vulnerabilities and threats, at least not at first! Also, don’t be overly fixated on “securing the systems” within the organization. The endeavor of tackling operational risk focused on consequences in any critical infrastructure environment to include the complex Aviation ecosystem is challenging even for the most resourced entity but can be advanced though a simplified approach: identifying, binning, and prioritizing the infrastructure environment. While no two entities within a single element of the 16 critical infrastructure sectors are exactly alike when it comes to risk, there is a basic process to move toward a greater understanding of operational risk through becoming more informed about the infrastructure environment in which the entity exists. The process starts with bringing internal and external stakeholders and subject matter experts together to analyze key areas such as Information Technology (IT) and Operational Technology (OT) components and points of convergence, analyzing internal and external cyber and physical dependencies, accounting for explosive growth in devices and wireless technology, and leveraging the contributions of people inside and outside the operational environment. Attaining a common understanding of the infrastructure environment as part of addressing consequences within operational risk is not easy to do or resource light, but the process outlined provides the framework to further any entity’s efforts in this space. When it comes to cyber risks, before an organization can consider vulnerabilities within and threats to its operations, it must first have a solid understanding of the consequences existing inside its infrastructure environment. Idaho National Lab’s Consequence-Driven, Cyber-Informed Engineering is offered as an example of this approach to effective and efficient cyber risk mitigation.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Hypervelocity impact flash expansion geometry under various spacecraft surface electrical conditions

A more congested space environment due to increasing space activities introduces new threats to spacecraft operators. Among these threats include hypervelocity impacts from microparticles (< 1 µg) in the form of meteoroids and space debris. These microparticles travel at speeds between 11.2 and 72.8 km/s with respect to the Earth and can impact spacecraft forming a small (~1 µm) and dense (~ 10 26 m -3 ) plasma. This plasma can generate a strong optical emission (impact flash) and a radio frequency (RF) emission. These emissions can lead to spacecraft electrical anomalies when the impacted spacecraft surface (target) carries high electrical potential due to various space weather effects. To understand the microparticle hypervelocity impact plasma and its associated threat to spacecraft electronics, we studied the hypervelocity impact flash expansion geometry under various spacecraft surface electrical conditions. Three high-speed broadband photomultiplier tubes (PMT) are used to capture the temporal evolution of the impact flash and the temporal evolution of the angular distribution of the impact flash expansion geometry in a 3 MV electrostatic dust accelerator during a ground-based experiment. Overall, results indicate that the impact surface electrical condition has a statistically significant influence on the impact flash geometry, and a strong similarity between the impact plasma and flash expansion geometry. Thus, this paper provides new experimental support for the impact flash origin from and connection with the impact plasma, and serves as the first impact flash expansion geometry characterization under various impact surface electrical conditions in a collisionless environment (< 10 -5 Torr).

42 ENGINEERING↗
DOE OSTI2023

Modeling, testing, and mitigation of electromagnetic pulse on PV systems

Electromagnetic Pulse (EMP) poses a significant threat to the normal operation of power systems, especially with the increasing penetration of renewable energy. Without adequate protection, EMP can severely damage equipment or result in circuit breakdowns or short circuits. Solar photovoltaic (PV) facilities are particularly susceptible to EMP since PV systems are outdoors and exposed to EMP radiation. To assess and mitigate this threat, this paper summarizes various models and tests used to study the effects of EMP on PV systems, assesses the nature of the threat, and identifies measures to mitigate it. The paper provides a comprehensive review by categorizing analytical methods based on their pros and cons, introducing and describing EMP-related events, and providing a taxonomy of analytical methods for studying EMP. This paper compares the processes of modeling, testing, and mitigating EMP at both the component and system levels of PV systems. Furthermore, it also presents a case study that reveals the vulnerability of solar inverters to EMP using the pulse current injection method. Finally, the paper discusses some of the remaining challenges that should be considered in future solar PV system design and deployment.

14 SOLAR ENERGY↗
DOE OSTI2021

Carbon Dioxide Conversion to Nanomaterials: Methods, Applications, and Challenges

Anthropogenic carbon dioxide (CO 2 ) emission is one of the biggest global threats that we are confronted with in the 21st century. A lack of prompt action to mitigate the atmospheric CO 2 level could lead to global catastrophic events. As a result of the significance of the aforementioned threat, multiple nations have agreed to enact carbon capture, storage, utilization, and sequestration (CCUS) technologies at academic and industrial scales with the aim of lowering the atmospheric CO 2 level. Although there are many reviews on CCUS technologies, there is a lack of comprehensive review on CO 2 conversion to more economically valuable products, such as nanomaterials. Carbon dioxide capture and conversion into nanomaterials is an interesting research topic in many ways because it contributes to our fundamental knowledge of material conversion, provides alternative ways to reduce atmospheric pollution, and yields lucrative products, which has not been explored broadly. Aside from the positive outcomes, we have a moral obligation to rectify a global threat caused by anthropogenic emission. Herein, we present current methods of converting CO 2 into organic and inorganic nanomaterials with a focus on operating conditions and challenges as well as the potential of nanomaterials in specifically biomedical applications as opposed to extensively reviewed energy-related uses. Furthermore, our review emphasizes the toxicity issues related to using such nanomaterials in biological settings based on literature and other comparable studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enhancing the Survivability of Power Systems With Grid-Edge DERs Against DoS Attacks

Power system survivability, defined as the ability of a system to maintain steady-state functionality under varying operational conditions, reflects its resilience against disturbances. While existing research primarily focuses on physical-layer disturbances, the increasing prevalence of grid-edge DERs, which are primarily used for integrating renewable energy, has significantly expanded the cyber attack surface. As a result, operational disruptions caused by cyber threats are posing significant challenges to system survivability and cannot be overlooked. To fill this gap, we redefine system survivability to incorporate the cyber layer’s status and propose a Distributionally Robust Optimization (DRO) approach to enhance power system survivability against potential cyber-physical threats. In this paper, we first analyze the operational guidelines of systems with a high penetration of DERs under various cyber network conditions and redefine survivability in this context. Next, we focus on the most common cyber threat, Denial-of-Service (DoS) attacks, and develop a corresponding attack model. This model allows for the creation of a kernel-based ambiguity set that captures attack uncertainties using historical data. Finally, we transform the proposed DRO model as a tractable optimization problem, with its solution providing an optimal cyber redundancy plan to enhance system survivability in DoS attack scenarios. Simulation results on the IEEE 13-node and 123-node test feeders demonstrate the effectiveness of our proposed model in improving system survivability. This model can also be expanded to include other types of common attacks and serve as a comprehensive planning tool to improve overall cyber physical survival of the system.

cybersecurity↗
DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗
DOE OSTI2023

Quantitative Power System Resilience Metrics and Evaluation Approach

Power system resilience is an emerging topic and plays an essential role in helping the power industry understand and respond to the increasing threats of extreme weather events. The first step of power system resilience analysis is to introduce metrics to quantify the resilience reasonably. Existing resilience metrics are typically restrained by the limited data for extreme event modeling and fall short in terms of physical interpretation and comparability. This paper develops novel quantitative metrics to evaluate power system resilience in pre- and post-event contexts. The developed metrics illustrate clear physical meanings and can be effectively used to compare resilience across different systems under different extreme events. Moreover, the developed metrics can be applied to both transmission and distribution systems. Simulation on a distribution system is employed to validate the effectiveness of the proposed resilience metrics and resilience evaluation approach.

power system resilience↗
DOE OSTI2023

Building water resilience in the face of cascading wildfire risks

Severe wildfire is altering the natural and the built environment and posing risks to environmental and societal health and well-being, including cascading impacts to water systems and built water infrastructure. Research on wildfire-resilient water systems is growing but not keeping pace with the scale and severity of wildfire impacts, despite their intensifying threat. In this study, we evaluate the state of knowledge regarding wildfire-related hazards to water systems. We propose a holistic framework to assess interactions and feedback loops between water quality, quantity, and infrastructure hazards as determinants of post-fire water availability and access. Efforts to address the evolving threat of wildfires to water systems will require more interdisciplinary research on the complex relationships shaping wildfire’s threat to water availability and access. To support this, we need reliable long-term data availability, consistent metrics, greater research in shared contexts, more extensive research beyond the burn area, and multistakeholder collaboration on wildfire risks to water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

GridSTIX

SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem

Blakely, Benjamin [Argonne National Laboratory (AN↗
DOE OSTI2021

Evolution and Trends of Industrial Control System Cyber Incidents since 2017

The industrial control systems (ICSs) that manage our critical infrastructure are increasingly converging with corporate networks and the Internet as technology and businesses prioritize digital connectivity. These connections make them more vulnerable and available to malicious cyber actors who traditionally targeted the companies’ more public-facing information technology (IT) networks. This paper will review select publicly reported cyber incidents to highlight the continued and growing threat to ICS devices and operational technology (OT) environments. It will summarize the incident and when available, will provide information on the cyber actors, the vulnerabilities they exploited, and any publications the U.S. Government (USG) provided in response. Data belonging to the Department of Homeland Security (DHS) will be used to highlight quantitative trends concerning ICS incidents. This paper builds on “History of Industrial Control System Cyber Incidents” (Hemsley & Fisher 2018), a paper that highlighted select noteworthy threats and incidents to ICS systems up to 2017. This paper will similarly review select incidents occurring after the last previously reviewed incident, Triton/HatMan, December 2017, and will note ICS incident trends including IT/OT convergence and advances in cyber-threat actors’ capabilities in observed in the examined incidents.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

SEDONA SpEctroscopic Detection Of Nerve Agents

Although the threat of a liquid explosive attack on a passenger aircraft has been mitigated by limiting the size of carry-on bottles, highly potent chemicals (e.g., nerve agents) are a very serious threat. A single travel bottle full of such chemicals would cause great harm to many people and create a national security incident disrupting civilian air travel. Current screening methods to detect highly potent chemicals require opening a closed bottle. Experts at Los Alamos National Laboratory have developed SEDONA, a low magnetic field nuclear magnetic resonance (NMR) to detect chemical threats through unopened bottles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Securing Vehicle Charging Infrastructure

As the US electrifies the transportation sector, cyber attacks targeting vehicle charging could bring consequences to electrical system infrastructure. This is a growing area of concern as charging stations increase power delivery and must communicate to a range of entities to authorize charging, sequence the charging process, and manage load (grid operators, vehicles, OEM vendors, charging network operators, etc.). The research challenges are numerous and are complicated because there are many end users, stakeholders, and software and equipment vendors interests involved. Poorly implemented electric vehicle supply equipment (EVSE), electric vehicle (EV), or grid communication system cybersecurity could be a significant risk to EV adoption because the political, social, and financial impact of cyberattacks - or public perception of such - ripples across the industry and has lasting and devastating effects. Unfortunately, there is no comprehensive EVSE cybersecurity approach and limited best practices have been adopted by the EV/EVSE industry. There is an incomplete industry understanding of the attack surface, interconnected assets, and unsecured interfaces. Thus, comprehensive cybersecurity recommendations founded on sound research are necessary to secure EV charging infrastructure. This project is providing the power, security, and automotive industry with a strong technical basis for securing this infrastructure by developing threat models, determining technology gaps, and identifying or developing effective countermeasures. Specifically, the team is creating a cybersecurity threat model and performing a technical risk assessment of EVSE assets, so that automotive, charging, and utility stakeholders can better protect customers, vehicles, and power systems in the face of new cyber threats.

33 ADVANCED PROPULSION SYSTEMS↗