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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Mitigating Extremist Maritime Threats to Radiological Material Transport Vessels

The 21st century has experienced a rise in the threat of global radicalism and extremist organizations, and there has been oft-reported interest from these groups in obtaining or exploiting radiological materials. The threat of extremists acquiring radiological materials while in transit or sabotaging a transport vessel carrying materials at sea is one that requires increased attention. Transport is already one of the most vulnerable times for any cargo but including the difficulties in securing a large ship on the open ocean makes oceanic transport of radiological materials a space of elevated vulnerability for sabotage, theft, or other attacks. The risks of violent extremist attacks on trade ships and trading routes are serious, as shipping routes sustain the global economy, but an attack on a radiological transport vessel could be a magnitude worse, impacting national and international security. While radicalists have largely remained on land in the past due to minimal maritime expertise or inability to project power out of their immediate vicinity, the world has witnessed past attacks on ships such as the USS Cole and the MV Limburg and it is likely only a matter of time before groups extend further into the sea and engage in more maritime campaigns against material transport vessels. This paper suggests methods for increasing safety and security on oceanic transport voyages through behavioral science principles and insider threat recognition training, as well as a better understanding of adversarial and extremist psychology. By providing transport personnel with the knowledge and support to identify and respond to unique maritime threats by extremists, these principles and training suggestions should advance and increase security on the high seas.

Kinney, Justin↗

DOE OSTI2024

Linking Threat Agents to Targeted Organizations: A Pipeline for Enhanced Cybersecurity Risk Metrics

In this study, we present a methodology leveraging Large Language Models (LLMs) to transform Cybersecurity Threat Intelligence (CTI) narratives into actionable insights for individual organizations. Our approach automates the extraction of machine-readable adversary SKRAM (Skills, Knowledge, Resources, Authorities, and Motivation) attributes from open-source reports, extending LLM utility beyond typical interactions. This innovation enables precise, automated assessments of cybersecurity risks posed by various adversaries. Using a chain-of-thought and multi-shot prompting strategy, our methodology advances the automation of cybersecurity feature extraction for new machine-learning models that predict the risk of adversary targeting. This approach is refined using a substantial dataset of over 150 analyst-validated threat reports and synthetic organizational data from 900 companies. Here, by bootstrapping the training data with a rule-based heuristic over synthetic data, we have developed a high-accuracy machine-learning model that allows entities to dynamically prioritize threats and defensive actions.

Cyber Threat Intelligence↗

DOE OSTI2024

A Privacy-Preserving Cyber Threat Intelligence Sharing System

Cyber Threat Intelligence (CTI) is a key resource for developing defensive strategies against potential cyber adversaries. Entities typically access CTI through open-source platforms, national agencies, or specialized commercial services. However, the bi-directional exchange of CTI is hindered by organizational trust boundaries, which complicate the sharing processes between entities and CTI providers. Centralized CTI services benefit from receiving suspicious cyber observables such as IP addresses, domain names, and email addresses from various entities. The aggregation allows for the correlation of widespread adversarial activities to enhance the alert and response mechanisms across the network of involved parties. Despite these benefits, openly sharing such observables incurs potential legal, regulatory, and reputational risks for the disclosing entities.This paper introduces a system designed to facilitate the secure exchange of cyber observables across trust boundaries without compromising the anonymity of the sharing entities. Here, we propose an architecture that leverages common web protocols alongside zero-knowledge proofs to authenticate members while maintaining anonymity. Additionally, we outline a privacy model tailored for STIX (Structured Threat Information eXpression) cyber observables to minimize the risk of inadvertently disclosing private information. Through our threat models, we assess the privacy implications of our proposed system and demonstrate its potential to enhance collaborative cyber defense efforts without exposing entities to undue risk.

BBS+ Signatures↗

NASA NTRS2017

Near Earth Asteroid Characterization for Threat Assessment

Physical characteristics of NEAs are an essential input to modeling behavior during atmospheric entry and to assess the risk of impact but determining these properties requires a non-trivial investment of time and resources. The characteristics relevant to these models include size, density, strength and ablation coefficient. Some of these characteristics cannot be directly measured, but rather must be inferred from related measurements of asteroids and/or meteorites. Furthermore, for the majority of NEAs, only the basic measurements exist so often properties must be inferred from statistics of the population of more completely characterized objects. The Asteroid Threat Assessment Project at NASA Ames Research Center has developed a probabilistic asteroid impact risk (PAIR) model in order to assess the risk of asteroid impact. Our PAIR model and its use to develop probability distributions of impact risk are discussed in other contributions to PDC 2017 (e.g., Mathias et al.). Here we utilize PAIR to investigate which NEA characteristics are important for assessing the impact threat by investigating how changes in these characteristics alter the damage predicted by PAIR. We will also provide an assessment of the current state of knowledge of the NEA characteristics of importance for asteroid threat assessment. The relative importance of different properties as identified using PAIR will be combined with our assessment of the current state of knowledge to identify potential high impact investigations. In addition, we will discuss an ongoing effort to collate the existing measurements of NEA properties of interest to the planetary defense community into a readily accessible database.

Asteroid characterization↗

NASA NTRSDate not supplied

A Survey of Cyber Threats and Security Controls Analysis for Urban Air Mobility Environments

Since the cyber threat landscape changes daily, cybersecurity needs to be an ongoing activity for every organization within the UAM environments. This paper will provide information on identified cyber threats and controls associated with an instance of the Urban Air Mobility (UAM) environment. The MITRE ATT&CK model and framework and the selection of cyber threats and the National Institute of Standards and Technology publications for security control identification and cybersecurity risk identification will be leveraged for analysis.

Cyber Threats↗

NASA NTRSDate not supplied

Cyber Threats & Security Controls Analysis for Urban Air Mobility Environments

Cyber Threats↗

DOE OSTI2023

Comparison of Socio-Technical Threat Models

Given the adoption of emerging technologies and the increasing complexity of managing such systems with a lifecycle much shorter than that of critical infrastructure systems, there is a practical need to be able to analyze sociotechnical dependencies and their associated evolving risks. Threat models based on social influence techniques can be used to implement adversarial tactics analogous to the cyber kill chain and attested to within the MITRE ATT&CK for ICS framework including Initial Access, Persistence, Collection, and Impact. Furthermore, as with cyber disruptions, the impact of social influence threat models can have an asymmetric impact that is not spatially-localized. Finally, unlike cyber attacks with a reasonably short duration (ransomware takes days to months), social influence based attacks have the potential to persist for much longer as they are based on long-term strategic infrastructure investments within the private sector. Given the increased importance of electric vehicle charging stations as a long-term, strategic infrastructure investment within the Energy and Transportation Sectors, we provide initial results that compare the impact of a Loss of Availability (T0826) realized through cyber and social influence based threat models. The analysis employs techniques from automated reasoning and measures of network complexity to understand evolving dominance of EV payment and charging networks within geographic region of interest. Within this context, we compare the impact of a loss of availability due to ransomware versus that of loss of support due to a merger and acquisition. Results across several different metro areas will be provided.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Threat Landscape for BESS and IBR

The cyber risk landscape for BESS and IBR can be broken up by threats, vulnerabilities, and consequences for these systems. This presentation walks through the cyber risk landscape for BESS through the lens of consequence-informed awareness and mitigation for each risk factor. Threats with varying capabilities have been demonstrated in real-world events. Though threat actors can rarely be directly influenced by organizations, exposure of systems to adversaries can be limited (a known issue with IBR systems) to reduce likelihood of adversaries accessing systems with disruptive consequences. Common trends in disclosed IBR vulnerabilities include weak password generation or managements for various devices or services and web portal vulnerabilities that provide unauthorized access to data or capabilities or elevated user privileges. Understanding these common vulnerabilities and considering the consequences if these types of vulnerabilities were to occur can help mitigate risk. Consequences range from loss-of-view events that have no reliability impact to asset damage or grid stability impacts. Five case studies are briefly shared to highlight trends in real-world events affecting IBR.

14 - SOLAR ENERGY↗

DOE OSTI2025

Cybersecurity Enhancement in Digital Substations: Hidden Markov Model-Based Smart Cyber Switching and Threat Response

The rising incidence of cyber-attacks on critical infrastructure and power grids poses significant threats to the stability and reliability of electrical substations, with potentially devastating consequences such as extended blackouts. This paper introduces an advanced cybersecurity framework aimed at safeguarding IEC 61850-based substations through the integration of software-defined networking (SDN) and digital twin (DT) technologies. The proposed DT-based framework employs smart cyber switching (SCS) for proactive threat mitigation and concurrent intelligent electronic device (CIED) for swift system restoration, thereby maintaining continuous operational integrity and robust cybersecurity defenses. Central to this framework is the adaptive port controller (APC), which enables dynamic port management to adapt to evolving threats, and an intrusion detection system (IDS) designed to detect and neutralize malicious attacks on IEC 61850-based sampled value (SV) and generic object-oriented substation event (GOOSE) messages within the substation’s communication network. Further, novel predictive intrusion detection and response (PIDR) algorithm is implemented on a digital substation (DS) to predict the best route to be taken by the attacker. The efficacy of these comprehensive cybersecurity frameworks is validated through rigorous simulations and a hardware-in-the-loop (HIL) testbed, showcasing the system’s ability to sustain substation operations amidst cyber-attacks.

Digital substation↗

DOE OSTI2022

IRAD-MPE Radiological and Nuclear Security Threats (Day 1) [Slides]

This module is designed to enhance awareness regarding radiological and nuclear security threats and the types of radioactive materials that can be used for criminal purposes or terrorist acts. The goals are to: (1) Review the Threat Assessment Process for MPEs, (2) Recognize Potential Radiological and Nuclear Security Threats, (3) Understand the basics of Radiological Dispersal Devices (RDD) and Radiological Exposure Devices (RED), (4) Learn about Medical, Commercial, and Naturally Occurring Radioactive Materials (NORM) sources, and (5) Understand the term Material Out of Regulatory Control (MORC).

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2022

Resolving Lipid Structures for Threat-Agnostic Signatures

Development of threat-agnostic biosignatures is critical for the detection of and response to biological threats that go beyond the historical list-based approach. Lipids are a class of structurally diverse biomolecules that hold great promise as relevant threat-agnostic biosignatures, yet the fundamental challenge of resolving and decoding structural differences among lipids remains an obstacle in the pursuit of signature development. Structural analysis of complex lipids remains stymied due to spectral complexity and the inability to resolve low abundance lipids. To address these challenges, we integrated ozonolysis with ion mobility mass spectrometry (IMS-MS) analysis to determine the structural information for complex lipid species and (2) reduced lipid sample complexity prior to introduction into the IMS-MS using normal phase high pressure liquid chromatography (HPLC) to enable the ozonolysis of low abundance lipids. We applied these new capabilities to define the lipid structures in antimicrobial resistant (AMR) and antimicrobial susceptible (AMS) biothreat organism Yersinia pestis and cells infected with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) variants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Fusion Centers and State Energy Stakeholders: Pathways to Robust Threat Information Sharing

Threats to our nation’s critical infrastructure are escalating in frequency and sophistication. It is essential for public and private sectors to join forces to understand the threats, mitigate risks, and plan to respond and recover from disruption. Fusion centers — organizations purpose-built to facilitate communication and cooperation between federal, state, local, and territorial law enforcement entities — are well-positioned to play a pivotal role in this context. Although fusion centers historically focused on crime and terrorism, there is a need to engage more broadly and build stronger threat information sharing relationships among energy stakeholders within their states.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Responsible Artificial Intelligence for Insider Threat Mitigation

This report examines the application of artificial intelligence (AI) technologies for insider threat mitigation (ITM) programs in nuclear security facilities. Insider threat detection presents unique challenges due to the subtle and adaptive nature of these threats, the complex signatures involved, and the scarcity of available data for analysis. Traditional human-centered approaches, while essential, face limitations in processing large amounts of data continuously and detecting subtle patterns across multiple systems. AI technologies can potentially address these limitations by providing 24/7 monitoring capabilities, identifying complex patterns that might escape human observation, and offering consistent application of security criteria. However, the deployment of AI in nuclear security contexts introduces significant new risks, including workflow disruption, expanded attack surfaces, potential for misuse, and ethical concerns regarding privacy, fairness, transparency, safety, and security. The high-consequence nature of nuclear security decisions demands careful consideration of these risks and systematic approaches to their mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2022

Survey of Cybersecurity Governance, Threats, and Countermeasures for the Power Grid

The convergence of Information Technologies and Operational Technology systems in industrial networks presents many challenges related to availability, integrity, and confidentiality. In this paper, we evaluate the various cybersecurity risks in industrial control systems and how they may affect these areas of concern, with a particular focus on energy-sector Operational Technology systems. There are multiple threats and countermeasures that Operational Technology and Information Technology systems share. Since Information Technology cybersecurity is a relatively mature field, this paper emphasizes on threats with particular applicability to Operational Technology and their respective countermeasures. We identify regulations, standards, frameworks and typical system architectures associated with this domain. We review relevant challenges, threats, and countermeasures, as well as critical differences in priorities between Information and Operational Technology cybersecurity efforts and implications. These results are then examined against the recommended National Institute of Standards and Technology framework for gap analysis to provide a complete approach to energy sector cybersecurity. We provide analysis of countermeasure implementation to align with the continuous functions recommended for a sound cybersecurity framework.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Could a Kilonova Kill: A Threat Assessment

Abstract Binary neutron star mergers produce high-energy emissions from several physically different sources, including a gamma-ray burst (GRB) and its afterglow, a kilonova (KN), and, at late times, a remnant many parsecs in size. Ionizing radiation from these sources can be dangerous for life on Earth-like planets when located too close. Work to date has explored the substantial danger posed by the GRB to on-axis observers; here we focus instead on the potential threats posed to nearby off-axis observers. Our analysis is based largely on observations of the GW170817/GRB 170817A multi-messenger event, as well as theoretical predictions. For baseline KN parameters, we find that the X-ray emission from the afterglow may be lethal out to ∼1 pc and the off-axis gamma-ray emission may threaten a range out to ∼4 pc, whereas the greatest threat comes years after the explosion, from the cosmic rays accelerated by the KN blast, which can be lethal out to distances up to ∼11 pc. The distances quoted here are typical, but the values have significant uncertainties and depend on the viewing angle, ejected mass, and explosion energy in ways we quantify. Assessing the overall threat to Earth-like planets, KNe have a similar kill distance to supernovae, but are far less common. However, our results rely on the scant available KN data, and multi-messenger observations will clarify the danger posed by such events.

Astronomy & Astrophysics↗

NASA NTRS2008

Mapping Historic Gypsy Moth Defoliation with MODIS Satellite Data: Implications for Forest Threat Early Warning System

This viewgraph presentation reviews a project, the goal of which is to study the potential of MODIS data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement satellite data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use MODIS time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.

Spurce, Joseph P.↗

NASA NTRS2008

Use of Vertically Integrated Ice in WRF-Based Forecasts of Lightning Threat

Previously reported methods of forecasting lightning threat using fields of graupel flux from WRF simulations are extended to include the simulated field of vertically integrated ice within storms. Although the ice integral shows less temporal variability than graupel flux, it provides more areal coverage, and can thus be used to create a lightning forecast that better matches the areal coverage of the lightning threat found in observations of flash extent density. A blended lightning forecast threat can be constructed that retains much of the desirable temporal sensitivity of the graupel flux method, while also incorporating the coverage benefits of the ice integral method. The graupel flux and ice integral fields contributing to the blended forecast are calibrated against observed lightning flash origin density data, based on Lightning Mapping Array observations from a series of case studies chosen to cover a wide range of flash rate conditions. Linear curve fits that pass through the origin are found to be statistically robust for the calibration procedures.

McCaul, E. W., jr.↗

NASA NTRS2010

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornadoes, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Spruce, Joseph P.↗