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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

An Integrated Physics-Based Risk Model for Assessing the Asteroid Threat

Although most asteroids and other near-Earth objects (NEOs) do not pose a threat to Earth’s inhabitants, impacts from objects that are just tens of meters in diameter can cause significant damage if they occur over a populated area. This paper forms the foundation of an effort at NASA Ames Research Center to quantify these risks and identify the greatest risk-driving parameters and uncertainties. An integrated risk model that couples dynamic probabilistic simulations of strike occurrences with physics-based models of NEO impact damage factors has been developed to generate casualty estimates for a range of NEO impact properties. Currently, the model focuses on the risk due to blast overpressure damage from airbursts and impacts on land. The model is first used to reproduce results from established sources, and then is extended to perform sensitivity studies that yield greater insights into risk driving parameters. Results show that meteor strength and entry angle play a role for small to mid-size NEOs, and that accounting for the specific target location significantly affects casualty estimates and dominates the risk. Future work will continue to refine and expand the models to better characterize key impact risk factors, include additional types of threats such as tsunamis and climate effects, and ultimately support assessments of potential asteroid mitigation strategies.

Asteroid Threat↗
DOE OSTI2011

Social/Ethical Issues in Predictive Insider Threat Monitoring

Combining traditionally monitored cybersecurity data with other kinds of organizational data is one option for inferring the motivations of individuals, which may in turn allow early prediction and mitigation of insider threats. While unproven, some researchers believe that this combination of data may yield better results than either cybersecurity or organizational data would in isolation. However, this nontraditional approach creates a potential conflict between goals, such as conflicts between organizational security improvements and individual privacy considerations. There are many facets to debate. Should warning signs of a potential malicious insider be addressed before a malicious event has occurred to prevent harm to the organization and discourage the insider from violating the organization’s rules? Would intervention violate employee trust or legal guidelines? What about the possibilities of misuse? Predictive approaches cannot be validated a priori; false accusations can affect the career of the accused; and collection/monitoring of certain types of data may affect employee morale. In this chapter, we explore some of the social and ethical issues stemming from predictive insider threat monitoring and discuss ways that a predictive modeling approach brings to the forefront social and ethical issues that should be considered and resolved by stakeholders and communities of interest.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Cyber Threat Screening Using a Queuing-Based Game-Theoretic Approach

Dynamic and uncertain security environments, such as cyber systems, often involve strategic interactions among multiple decision-making agents. In this paper, we consider a cybersecurity setting where a system administrator (defender) has to screen malicious service requests of an attacker who seeks to exhaust available cyber resources and inconvenience users with normal requests. We propose a novel cyber-threat inspection model, based on Stackelberg games, that unies aspects of Threat Security Games with the Erlang-B queuing framework to provide equilibrium strategies for both the attacker and defender. In our proposed model, the defender seeks to determine the optimal number of inspection nodes required to maximize detection probability of malicious requests, while the attacker maximizes the probability of legitimate requests dropping out of the system. We derive analytical expressions of the equilibrium solutions of the proposed Stackelberg game under realistic assumptions on system observability and payoff structure of the players. A numerical case study is presented, and steps for further research are identified.

Cybersecurity, Stackelberg game, Erlang-B loss sys↗
DOE OSTI2024

Cyber Threat Assessment of Solar PV Energy

This presentation discusses cyber threats to solar energy systems. Through a discussion of the cyber risk elements of threat, vulnerability, and consequence, we present examples of these risks in the solar industry. Then, we present 8 real-world events from the last 5 years that have affected the solar industry or solar companies.

14 SOLAR ENERGY↗
DOE OSTI2025

Energy Sector Threat Brief: Trends and Incidents

This is a threat brief of cyber incidents and trends affecting the global energy sector over the last 12 months and resources for threat sharing, targeting an audience of utility cyber and physical security stakeholders.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Scout: An AI-Driven Tool for Cyber Threat Report Creation

This talk will introduce Scout, an AI-driven tool designed to enhance the efficiency of cyber threat report creation. Attendees will learn how Scout leverages advanced AI technologies to streamline the reporting process, thereby enabling faster and more reliable threat assessments.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Evaluation of dried blood spot sampling for verification of exposure to chemical threat agents

Abstract Purpose Exposure to chemical threat agents (CTAs), including nerve agents, the vesicating agent sulfur mustard, and opioids, remains a significant threat to warfighter and civilian populations. Definitive analytical methods to verify exposure to CTAs require shipping refrigerated or frozen biomedical samples to reference laboratories for analysis. Logistical and financial burdens arise as the transport of biomedical samples is subject to strict restrictions and complex packaging, which, if done incorrectly, can lead to sample deterioration. The use of dried blood spot (DBS) sampling could provide operational improvements for collecting, storing, and shipping important forensic samples. Therefore, this effort focuses on developing DBS techniques with Mitra® 30-µL volumetric absorptive microsampling (VAMS®) devices for use in CTA exposure verification. Methods VAMS® devices were loaded and dried with human whole blood that was exposed to the metabolites pinacolyl methylphosphonic acid (PMPA), ethyl methylphosphonic acid (EMPA), 1,1’sulfonylbis[2-(methylsulfinyl)ethane] (SBMSE), norfentanyl, norcarfentanil, norsufentanil, and norlofentanil. Following extraction from the VAMS® devices, metabolites were detected using liquid chromatography-tandem mass spectrometry (LC–MS/MS). The methods were validated for performance by assessing sensitivity, precision, accuracy, and recovery. Results These methods were sensitive to 1 ng/mL for SBMSE, 0.5 ng/mL for PMPA, EMPA, and norfentanyl; 0.1 ng/mL for norlofentanil, and 0.05 ng/mL for norsufentanil and norcarfentanil. All methods met acceptable precision and accuracy criteria with favorable recovery. Conclusions These results demonstrated the utility of VAMS® in stabilizing human whole blood and show promise as an improved collection method for verification of exposure to various CTAs.

Toxicology↗
DOE OSTI2025

Numerical simulation of asteroid geometry variance on airburst threat

For an atmospheric airburst the primary source of concern when assessing uncertainty is the size and velocity. Determining these properties provides the basis for threat assessment, as the total energy of the asteroid may then be estimated, and the threat investigated thoroughly. Even with clarity as to how much energy an asteroid may deposit, a great deal of uncertainty still exists for the actual energy deposition process. One such source of uncertainty is the geometry of the incoming asteroid. The geometry of an asteroid will alter the stress distribution during entry, which adds uncertainty to when fracture will occur. Here, in this study, we use Smoothed Particle Hydrodynamics to model the atmospheric airburst of Tunguska-scale asteroids with varying geometric profiles, including a sphere, ellipsoid, binary and superellipsoid. Each asteroid is modeled as a homogenous structure with strength. We assess uncertainty through a series of planar 2D simulation cases for each geometry, comparing the source of stochasticity across geometries. A single 3D airburst simulation for each geometry is also analyzed. Additionally, the 3D cases are compared to the highly uncertain Tunguska event, predicting variance in burst height across geometries, but all bounded by theoretical burst heights proposed for Tunguska.

Airburst↗
DOE OSTI2023

Metal toxin threat in wildland fires determined by geology and fire severity

Accentuated by climate change, catastrophic wildfires are a growing, distributed global public health risk from inhalation of smoke and dust. Underrecognized, however, are the health threats arising from fire-altered toxic metals natural to soils and plants. Here, we demonstrate that high temperatures during California wildfires catalyzed widespread transformation of chromium to its carcinogenic form in soil and ash, as hexavalent chromium, particularly in areas with metal-rich geologies (e.g., serpentinite). In wildfire ash, we observed dangerous levels (327-13,100 µg kg -1 ) of reactive hexavalent chromium in wind-dispersible particulates. Relatively dry post-fire weather contributed to the persistence of elevated hexavalent chromium in surficial soil layers for up to ten months post-fire. The geographic distribution of metal-rich soils and fire incidents illustrate the broad global threat of wildfire smoke- and dust-born metals to populations. Our findings provide new insights into why wildfire smoke exposure appears to be more hazardous to humans than pollution from other sources.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2014

TH-A-12A-01: Medical Physicist's Role in Digital Information Security: Threats, Vulnerabilities and Best Practices

I. Information Security Background (Speaker = Kevin McDonald) Evolution of Medical Devices Living and Working in a Hostile Environment Attack Motivations Attack Vectors Simple Safety Strategies Medical Device Security in the News Medical Devices and Vendors Summary II. Keeping Radiation Oncology IT Systems Secure (Speaker = Bruce Curran) Hardware Security Double-lock Requirements “Foreign” computer systems Portable Device Encryption Patient Data Storage System Requirements Network Configuration Isolating Critical Devices Isolating Clinical Networks Remote Access Considerations Software Applications / Configuration Passwords / Screen Savers Restricted Services / access Software Configuration Restriction Use of DNS to restrict accesse. Patches / Upgrades Awareness Intrusion Prevention Intrusion Detection Threat Risk Analysis Conclusion Learning Objectives: Understanding how Hospital IT Requirements affect Radiation Oncology IT Systems. Illustrating sample practices for hardware, network, and software security. Discussing implementation of good IT security practices in radiation oncology. Understand overall risk and threats scenario in a networked environment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2012

Proactive Defense for Evolving Cyber Threats

There is great interest to develop proactive methods of cyber defense, in which future attack strategies are anticipated and these insights are incorporated into defense designs; however, little has been done to place this ambitious objective on a sound scientific foundation. Indeed, even fundamental issues associated with how the “arms race” between attackers and defenders actually leads to predictability in attacker activity, or how to effectively and scalably detect this predictability in the relational/temporal data streams generated by attacker/defender adaptation, haven’t been resolved. This LDRD project addressed many of these challenges and the results are briefly summarized here. We have characterized the predictability of attacker/defender coevolution and have leveraged our findings to create a framework for designing proactive defenses for large (organizational) networks. More specifically, this project applied rigorous predictability-based analytics to two central and complementary aspects of the network defense problem – attack strategies of the adversaries and vulnerabilities of the defenders’ systems – and used the results to develop a scientifically-grounded, practically-implementable methodology for designing proactive cyber defense systems. Briefly, predictive analysis of attack strategies involved first conducting predictability assessments to characterize attacker adaptation patterns in given domains, and then used these patterns to “train” adaptive defense systems capable of providing robust performance against both current and (near) future threats. The problem of identifying and prioritizing defender system vulnerabilities was addressed using statistical and machine learning to analyze a broad range of data (e.g., cyber, social media) on recently detected system vulnerabilities to “learn” classifiers that predict how likely it is that, and how soon, new vulnerabilities will be exploited. A variety of cyber threat case studies were developed and investigated throughout the project, one selected from the cyber security research community and one that is more comprehensive and of higher priority to SNL and to external national security partners. A sample of research results and application of this methodology are included in this report (as a series of peer-reviewed publications). For ease of reference the title and SAND number are included below.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Cyber Security Lecture Series: The CERT Insider Threat Guide [Slides]

Methodology: - Analysis of Analysis of >700 documented insider threat 700 documented insider threat cases; - Root cause Root cause analysis; - Mapping to NIST 800-53; - Detailed mapping to common organizational roles and responsibilities.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Dogs That Haven't Barked: Towards an Understanding of the Absence of Expected Technological Threats Workshop Bibliography

Lawrence Livermore National Laboratory’s Center for Global Security Research hosted a workshop to investigate why some consistently predicted threats from science and technology (S&T) have not manifested with the impacts to international security as forecasted. During the workshop, “Dogs That Haven’t Barked: Towards an Understanding of the Absence of Expected Technological Threats,” participants used two specific cases to focus the discussion: biotechnology and man-portable air defense systems (MANPADS).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Radiological/Nuclear (RN) Terrorism: Global Assessment of Threat Intention Drivers.

There is a pressing need in international security policy to better understand the future landscape of radiological and nuclear (RN) dangers and how best to target resources to affect their reduction. The highly dynamic nature of the global geopolitical, social and technological environments means that ther e are many potential forces that might influence the magnitude of current RN dangers, especially those emanating from non-state actors like terrorists. These include: the spread of radical ideology, the growth of civilian nuclear energy in politically unstable regions of the world, the potential for increased nuclear proliferation in those regions, the continued dissemination of WMD information in open sources, and advances in technology that may facilitate VNSA violent non-state actor (VNSA) RN programs. Therefore, this study’s main purpose is to provide an overview of the high level future drivers of RN terrorism as they pertain to the motives and intentions1 of known and potential adversaries. A central approach of this study is to ask the question: Why have there not been more attempts to engage in RN terrorism and, particularly in the case of radiological terrorism, why have those attempts that have been made not been more successful? Once the probable factors that have curtailed the RN terrorist threat thus far have been identified, the study will consider whether there are extant and emerging drivers that might bring about changes in these mitigating factors over the next 10 years. Finally, the study attempts to assess the future dangers of RN terrorism based on these potential changes and what policy approaches can be implemented to reduce the threat, particularly the role of deterrence and dissuasion.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Radiological Exposure Devices (RED) Technical Basis for Threat Profile

Facilities that manufacture, store or transport significant quantities of radiological material must protect against the risk posed by sabotage events. Much of the analysis of this type of event has been focused on the threat from a radiological dispersion device (RDD) or "dirty bomb" scenario, in which a malicious assailant would, by explosives or other means, loft a significant quantity of radioactive material into a plume that would expose and contaminate people and property. Although the consequences in cost and psychological terror would be severe, no intentional RDD terrorism events are on record. Conversely, incidents in which a victim or victims were maliciously exposed to a Radiological Exposure Device (RED), without dispersal of radioactive material, are well documented. This paper represents a technical basis for the threat profile related to the risk of nefarious use of an RED, including assailant and material characterization. Radioactive materials of concern are detailed in Appendix A.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Advanced Diagnostic and Sample Preparation Platform for Early Threat Surveillance

Emerging infectious diseases present a profound threat to global health, economic development, and political stability, and therefore represent a significant national security concern for the United States. The increased prevalence of international travel and globalized trade further amplify the threat of infectious disease outbreaks of catastrophic effect. The key to containing and eradicating an outbreak before it goes global is rapid identification of index cases and initial clusters of affected individuals. This depends upon establishment of a biosurveillance network that effectively reaches infectious disease hotspots in even the most remote regions of the world and provides a network-integrated, location-appropriate diagnostic capability. At present, there are two critical needs which must be addressed in order to extend biosurveillance activities beyond centralized laboratory facilities: 1) A simple, reliable, and safe method for immediate stabilization of clinical specimens in the field; and 2) A flexible sample processing platform that enables in-field preparation of clinical specimens for rapid, on-site analysis using a variety of diagnostic assay platforms. These needs are not necessarily mutually exclusive; in fact, we propose that they are most efficiently addressed by a deployable sample processing platform that immediately stabilizes the information content of clinical specimens through transformation of the inherently unstable analytes of interest into stable equivalents that are appropriately formatted for downstream analysis. In order to address this problem, we have developed a sample processing pipeline and microfluidics-based platform modules enabling: 1) Extraction of total RNA from finger-stick quantities of human whole blood; and 2) Microscale synthesis of appropriately-formatted cDNA products that capture the information content of blood RNA in a stable form that supports pathogen detection and/or characterization via PCR and/or Second Generation Sequencing (SGS). Through this research we have discovered new, effective solutions for problems that thus far have hindered use of digital microfluidics (DMF) in biomedical applications. Our work reveals a clear path forward to fieldable, automated sample processing systems that will enable rapid, on-site identification of usual-suspect and novel pathogens in clinical specimens for improved biosurveillance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Magnetic Detection of Chemical Threats

Los Alamos researchers have developed a technology to quickly detect chemical threats using a fieldable detector that provides real-time detection to ensure safety for warfighters, agricultural workers, and the general public. Traditional laboratory-based detection does not allow for agile response to threats on the battlefield or to our food supply chain. Our portable detector brings the laboratory to the field for real-time detection of chemical agents in samples without needing to send the samples to a remote location for analysis. This technology fits a market need in public safety, military sensor design, and pesticide detection. We have proven that this technology works on the benchtop, and are working to miniaturize the system to enable deployment. We are seeking qualified licensing or CRADA partners to finalize development of this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗