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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 OSTI2021

A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica

Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.

Fu, Yanyang↗
DOE OSTI2018

Insider Threat Cybersecurity Framework Webtool & Methodology: Defending Against Complex Cyber-Physical Threats

The paper demonstrates how the Insider Threat Cybersecurity Framework (ITCF) web tool and methodology help provide a more dynamic, defense-in-depth security posture against insider cyber-physical threats. ITCF includes over 30 cyber-physical security best practices to help organizations identify, protect, detect, respond and recover to sophisticated insider threats and vulnerabilities. The following paper tests the efficacy of this approach and helps validate and verify ITCF’s capabilities and features through various insider attacks use-cases. Three different investment scenarios and explored to determine how an organization can most efficiently leverage ICTF to increase their overall security posture against insider attacks. ITCF also facilitates implementation of the goals outlined in Presidential Executive Order (EO) on Strengthening the Cybersecurity of Federal Networks and Critical Infrastructure (May 2017): To help owners and operators of critical infrastructure identify, protect, detect, respond, and recover cyber threats. ITCF helps organizations with the following features: provides an easy to use rapid assessment tool to perform an insider threat self-assessment; determines the current insider threat cybersecurity posture; defines investment based goals to achieve a target state; connects the cybersecurity posture with business processes, functions, and continuity; and finally, helps develop plans to answer critical organizational cybersecurity questions. In this paper, the webtool and its core capabilities are depicted by performing an extensive comparative assessment over two different high-profile insider threat incidents.

Mylrea, Michael E.↗
DOE OSTI2019

“Defense by other means”: future evolution(s) of cooperative threat reduction

This article discusses likely future contexts of, and options for, global threat-reduction activities to support nonproliferation goals over the next five to ten years. Threat-reduction activities span a continuum from unilateral actions that the United States might take with little cooperation and transparency at one end to cooperative actions associated with negotiated treaties and agreements at the other. This study focuses on cooperative approaches embodied in the Cooperative Threat Reduction (CTR) program, which has been the most visible program reducing the threats posed by weapons of mass destruction for over two decades. Here, we argue that CTR’s evolution can be described in terms of the relationship between the desired US influence on outcomes, the ability to generate a common threat definition, and appetite for collaboration on threat reduction. To that end, this article provides an introduction and overview of CTR initiatives over its twenty-seven-year history and a review of relevant legislation and trends. After introducing and describing the CTR Possible Futures Framework, this article offers five possible options for—and discusses the implications of—CTR’s future evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗
DOE OSTI2026

NASA analysis of space mission options for the 2025 planetary defense conference hypothetical asteroid impact threat scenario

The 2025 Planetary Defense Conference (PDC) hypothetical asteroid impact threat exercise is being conducted in coordination with the United Nations-endorsed Space Mission Planning Advisory Group (SMPAG), exercising SMPAG's processes for assessing space mission options and communicating to decision makers. Here, in this paper, we describe the work performed by our NASA-led team and present the results we contributed to the SMPAG effort for the exercise. Our NASA-led team assessed mission options for asteroid reconnaissance (flyby and rendezvous), deflection, and robust disruption using several viable techniques: kinetic impactors, ion beam deflection, and nuclear explosive devices. Our simulations and analyses considered how much change-in-velocity an asteroid can tolerate before fragmentation onset, and we worked towards establishing requirements for robustly disrupting an asteroid. Heuristics informed by the simulation results are incorporated into optimization of deflection and disruption mission campaign options. Finally, we make some observations about useful generalizations from these results with potential applicability to any planetary defense scenario.

Asteroid deflection↗
DOE OSTI2016

The emerging threat of superwarfarins: history, detection, mechanisms, and countermeasures: The emerging threat of superwarfarins

Superwarfarins were developed following the emergence of warfarin resistance in rodents. Compared to warfarin, superwarfarins have much longer half-lives and stronger affinity to vitamin K epoxide reductase and therefore can cause death in warfarin-resistant rodents. By the mid-1970s, the superwarfarins brodifacoum and difenacoum were the most widely used rodenticides throughout the world. Unfortunately, increased use was accompanied by a rise in accidental poisonings, reaching >16,000 per year in the United States. Risk of exposure has become a concern since large quantities, up to hundreds of kilograms of rodent bait, are applied by aerial dispersion over regions with rodent infestations. Reports of intentional use of superwarfarins in civilian and military scenarios raise the specter of larger incidents or mass casualties. Unlike warfarin overdose, for which 1–2 days of treatment with vitamin K is effective, treatment of superwarfarin poisoning with vitamin K is limited by extremely high cost and can require daily treatment for a year or longer. Furthermore, superwarfarins have actions that are independent of their anticoagulant effects, including both vitamin K–dependent and –independent effects,which are not mitigated by vitaminKtherapy. In this review, we summarize superwarfarin development, biology and pathophysiology, their threat as weapons, and possible therapeutic approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A new method for imaging nuclear threats using cosmic ray muons

Muon tomography is a technique that uses cosmic ray muons to generate three-dimensional images of volumes using information contained in the Coulomb scattering of the muons. Advantages of this technique are the ability of cosmic rays to penetrate significant overburden and the absence of any additional dose delivered to subjects under study beyond the natural cosmic ray flux. Disadvantages include the relatively long exposure times and poor position resolution and complex algorithms needed for reconstruction. Furthermore, we demonstrate a new method for obtaining improved position resolution and statistical precision for objects with spherical symmetry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Exploring the Neurocircuitry Underpinning Predictability of Threat in Soldiers with PTSD Compared to Deployment Exposed Controls

Background: Prior work examining emotional dysregulation observed in posttraumatic stress disorder (PTSD) has primarily been limited to fear-learning processes specific to anticipation, habituation, and extinction of threat. In contrast, the response to threat itself has not been systematically evaluated. Objective: To explore potential disruption in fear conditioning neurocircuitry in service members with PTSD, specifically in response to predictable versus unpredictable threats. Method: In the current study, active-duty U.S. Army soldiers with (PTSD group; n = 38) and without PTSD (deployment-exposed controls; DEC; n = 40), participated in a fear-conditioning study in which threat predictability was manipulated by presenting an aversive unconditioned stimulus (UCS) that was either preceded by a conditioned stimulus (i.e., predictable) or UCS alone (i.e., unpredictable). Threat expectation, skin conductance response (SCR), and functional magnetic resonance imaging (fMRI) signal to predictable and unpredictable threats (i.e., UCS) were assessed. Results: Both groups showed greater threat expectancy and diminished threat-elicited SCRs to predictable compared to unpredictable threat. Significant group differences were observed within the amygdala, hippocampus, insula, and superior and middle temporal gyri. Contrary to our predictions, the PTSD group showed a diminished threat-related response within each of these brain regions during predictable compared to unpredictable threat, whereas the DEC group showed increased activation. Conclusion: Although, the PTSD group showed greater threat-related diminution, hypersensitivity to unpredictable threat cannot be ruled out. Furthermore, pre-trauma, trait-like factors may have contributed to group differences in activation of the neurocircuitry underpinning fear conditioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

GRiP - A flexible approach for calculating risk as a function of consequence, vulnerability, and threat.

Get a GRiP (Gravitational Risk Procedure) on risk by using an approach inspired by the physics of gravitational forces between body masses! In April 2010, U.S. Department of Homeland Security Special Events staff (Protective Security Advisors [PSAs]) expressed concern about how to calculate risk given measures of consequence, vulnerability, and threat. The PSAs believed that it is not 'right' to assign zero risk, as a multiplicative formula would imply, to cases in which the threat is reported to be extremely small, and perhaps could even be assigned a value of zero, but for which consequences and vulnerability are potentially high. They needed a different way to aggregate the components into an overall measure of risk. To address these concerns, GRiP was proposed and developed. The inspiration for GRiP is Sir Isaac Newton's Universal Law of Gravitation: the attractive force between two bodies is directly proportional to the product of their masses and inversely proportional to the squares of the distance between them. The total force on one body is the sum of the forces from 'other bodies' that influence that body. In the case of risk, the 'other bodies' are the components of risk (R): consequence, vulnerability, and threat (which we denote as C, V, and T, respectively). GRiP treats risk as if it were a body within a cube. Each vertex (corner) of the cube represents one of the eight combinations of minimum and maximum 'values' for consequence, vulnerability, and threat. The risk at each of the vertices is a variable that can be set. Naturally, maximum risk occurs when consequence, vulnerability, and threat are at their maximum values; minimum risk occurs when they are at their minimum values. Analogous to gravitational forces among body masses, the GRiP formula for risk states that the risk at any interior point of the box depends on the squares of the distances from that point to each of the eight vertices. The risk value at an interior (movable) point will be dominated by the value of one vertex as that point moves closer and closer to that one vertex. GRiP is a visualization tool that helps analysts better understand risk and its relationship to consequence, vulnerability, and threat. Estimates of consequence, vulnerability, and threat are external to GRiP; however, the GRiP approach can be linked to models or data that provide estimates of consequence, vulnerability, and threat. For example, the Enhanced Critical Infrastructure Program/Infrastructure Survey Tool produces a vulnerability index (scaled from 0 to 100) that can be used for the vulnerability component of GRiP. We recognize that the values used for risk components can be point estimates and that, in fact, there is uncertainty regarding the exact values of C, V, and T. When we use T = t{sub o} (where t{sub o} is a value of threat in its range), we mean that threat is believed to be in an interval around t{sub o}. Hence, a value of t{sub o} = 0 indicates a 'best estimate' that the threat level is equal to zero, but still allows that it is not impossible for the threat to occur. When t{sub o} = 0 but is potentially small and not exactly zero, there will be little impact on the overall risk value as long as the C and V components are not large. However, when C and/or V have large values, there can be large differences in risk given t{sub o} = 0, and t{sub o} = epsilon (where epsilon is small but greater than a value of zero). We believe this scenario explains the PSA's intuition that risk is not equal to zero when t{sub o} = 0 and C and/or V have large values. (They may also be thinking that if C has an extremely large value, it is unlikely that T is equal to 0; in the terrorist context, T would likely be dependent on C when C is extremely large.) The PSAs are implicitly recognizing the potential that t{sub o} = epsilon. One way to take this possible scenario into account is to replace point estimates for risk with interval values that reflect the uncertainty in the risk components. In fact, one could argue that T never equals zero for a man-made hazard. This paper describes the thought process that led to the GRiP approach and the mathematical formula for GRiP and presents a few examples that will provide insights about how to use GRiP and interpret its results.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Cyber Threat Metrics

Threats are generally much easier to list than to describe, and much easier to describe than to measure. As a result, many organizations list threats. Fewer describe them in useful terms, and still fewer measure them in meaningful ways. This is particularly true in the dynamic and nebulous domain of cyber threats - a domain that tends to resist easy measurement and, in some cases, appears to defy any measurement. We believe the problem is tractable. In this report we describe threat metrics and models for characterizing threats consistently and unambiguously. The purpose of this report is to support the Operational Threat Assessment (OTA) phase of risk and vulnerability assessment. To this end, we focus on the task of characterizing cyber threats using consistent threat metrics and models. In particular, we address threat metrics and models for describing malicious cyber threats to US FCEB agencies and systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

GraphCH: A Deep Framework for Assessing Cyber-Human Aspects in Insider Threat Detection

Insider threat is one of the most damaging cyber attacks that could cause the loss of intellectual property and enterprise data security breaches. Action sequence data such as host logs are used to investigate such threats and develop anomaly-based AI detectors. However, insider threat actions are similar to legitimate user activities, causing AI detectors to fail and suffer from high false alarm rates. Therefore, user cyber activity logs are inadequate to fully unfold insider threats. In this study, we adopt human psychological principles of risk-taking and impulsiveness along with host data to assess the influence and usefulness of human behavioral aspects in insider threat detection. Here, we hypothesize that individuals' impulsive and risk-taking behavior correlates with cyberspace activities. To validate our hypothesis, we conducted an IRB-approved study recruiting 35 participants who work in a large U.S. university and collected their cyber and psychological data for 90 days. Host and human-behavioral data analysis and mapping indicate that impulsive and risk-taking users trigger more system errors causing (un)intentional insider threats and are susceptible to attackers' social engineering and cognitive hacking. Utilizing cyber-human aspects, we introduce a Cyber-Human Graph Neural Network (GNN) based framework GraphCH to identify abnormal user behaviors and detect insider threats.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Domestic Extremism: Countering the Threat Posed to Critical Assets

Domestic extremism has been a growing concern in the United States 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 threat of insider attack and violence, creating a new threat to be countered in the Office of Radiological Security’s radiological source security mission. In this effort, 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 and next steps. Twenty-two subject matter experts participated in a series of five focus group sessions. Questions focused on definitions of domestic extremism, potential changes in the threat, best practices in securing facilities, assets, and personnel, and any perceived gaps. Upon completion of the focus groups, notes were analyzed thematically to identify any recurring patterns in the results. In addition, a review of academic, industry, and government literature was conducted to understand the threat, describe the process of radicalization to extremism, and to identify empirically informed practices in prevention and response. Results of this project demonstrated that further work is needed to define domestic extremism in law, regulation, and policy, to help the U.S. develop a consistent response to the threat within organizations. This is especially important, as SMEs emphasized the need for early intervention in prevention efforts, noting that organizations need clear guidance on when and how to intervene. In addition, the need for social media monitoring was discussed, although challenges remain to do so with appropriate respect for privacy and civil liberties concerns.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Security Self-Assessment Toolkit for Nuclear Materials Facilities: Focus on Insider Threat Mitigation

Theft or sabotage of weapons-usable nuclear materials is a global concern. To minimize this threat, establishing and maintaining an effective nuclear security regime is required to protect against criminal or other negligent acts. Use of a formalized insider threat mitigation program is one such security measure. Individuals who have or held authorized access to an organization's critical assets, such as nuclear materials, are considered "insiders." Insider threats, or insider adversaries, are motivated individuals who possess access, authority, and knowledge to conduct a malicious act or facilitate that of an external party. To thwart insider threats (both intentional and unintentional), organizations can formalize an enterprise-wide approach to identify and mitigate the unique risks presented by insiders. This report provides an approach to evaluate an insider threat mitigation program at facilities with nuclear materials. Formal program evaluations serve many purposes and can be designed using several different methods and techniques. This report presents a self-assessment approach to program evaluation whereby an organization can assess its strengths, identify key gaps, and set priorities for ongoing improvement efforts to mitigate insider threats. Results of the self-assessment can provide critical information to contribute to the continuous improvement of an organization’s insider threat mitigation program within eight specific domain areas.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

MetaPoL: Immersive VR based Indoor Patterns of Life (PoL) and Anomalies Data Generation for Insider Threat Modeling in Nuclear Security

Insider threats are perhaps the most serious challenges that nuclear and radiological security systems face. Insiders pose such a great threat due to their access, authority, and knowledge, granting them opportunities to bypass dedicated nuclear and radiological security elements. For example, in one of the latest major insider threat incidents to nuclear security, the Doel-4 nuclear powerplant in Belgium suffered a shutdown, the threat of nuclear materials diversion, and long-term loss of tens of millions of dollars. Seven years of investigation concluded that it was an inside job and attempted sabotage. In this regard, there is an immediate need for R&D and technology integration in the domain of modeling indoor Patterns-of-Life (PoL) and anomaly detection. This can be achieved by using datasets of facility users’ mobility and activity, which can support the design of algorithms for insider threat modeling and detection. However, due to classification, privacy, sensitivity, and safety protocols, such datasets from real physical nuclear reactor facilities are not only hard to share, but also not always feasible to deploy and collect. Aiming to find an alternate solution, our proposed demonstration work - MetaPoL, is the first-ever (for the application space) immersive VR (virtual reality) environment of a real-world secure facility and allows users to move-and-stay through the designed indoor physical layout and also encounter NPCs (non-player characters) that emulate other facility users. In the MetaPoL an interactive user performs realistic spatio-temporal movement, dwelling and activities using a Meta Quest Pro VR headset, and that generates high-frequency (in time) high-resolution (in space) indoor spatial-temporal datasets that are valuable for PoL modeling and anomaly detection research specifically for insider threat modeling and detection mission. Such generated realistic, rich in context, and mission specific datasets can boost AI/Machine Learning based research for modeling and detecting insider threats in nuclear security and nonproliferation.

Gunaratne, Chathika↗