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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Emerging Threats in Transportation Security Related to Intelligent Transportation Systems (ITS)

Transport of high-consequence shipments requires a resilient and robust systems of systems to guarantee cargo arrival. Furthermore, rising adoption of technologies such as connected and automated vehicles (CAVs), intelligent infrastructure, and vehicle-to-everything (V2X) communication presents unique challenges for securing transportation systems. Within these Intelligent Transportation Systems (ITS), several additional vulnerabilities exist that create pathways for adversarial attacks and cargo interception. For example, connectivity provides cyber pathways directly into vehicle systems and infrastructure for malicious actors. Furthermore, advanced vehicle automation exposes additional vehicle control necessary for shipment interception otherwise unavailable to adversaries. Within this paper, we will discuss the specific threats introduced by ITS-enabled technologies currently deployed and in development. These include those mentioned related to connectivity and automation, but will be expanded into grid, infrastructure, and vehicle specific threats. In addition, we will discuss how to potentially mitigate these emerging challenges as well as how to safeguard transportation systems from next generation attacks.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗
DOE OSTI2025

Cybersecurity for Digital Energy Infrastructure : Trends, Threats, and Cyber-Informed Engineering

This presentation discusses the rise in digital energy infrastructure and associated threats. It covers an in-depth risk assessment of digital energy equipment and provides real world examples of threats, vulnerabilities, and known incidents. Research conducted by INL assessing and addressing these risks follows, concluding with a dive into Cyber-Informed Engineering (CIE) and it's application to digital energy infrastructure, using battery energy storage systems (BESS) as an example.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Rapid simulation of X-ray scatter measurements for threat detection via GPU-based ray-tracing

Scatter-based X-ray imaging has increased in prominence in areas ranging from cancer diagnostics to threat detection in aviation security, due largely to the development of new algorithms and components over the last decade. However, system design and algorithm development are often hindered by an inability to generate a sucient amount of accurate data. To further the development of scatter-based systems, we created a rapid X-ray scatter simulation tool built with a GPU-centric, parallel ray-tracing framework (NVIDIA OptiX). This tool models a full range of X-ray imaging components and describes 3D objects formed with heterogeneous media using polygon meshes. The scatter simulation algorithm we used is similar to the previously-described hybrid approach; however, instead of employing Monte Carlo techniques, we developed a purely analytical algorithm to sample the distribution of single-scatter events throughout the region of interest. The contribution of scattered photons to the measured signal is then calculated using the first-Born approximation. Here, the accuracy of the implemented pipeline has been validated by comparing simulated against experimental data obtained with a laboratory X-ray scattering system and phantoms of varied materials. Using a single desktop computer with an NVIDIA GTX 770 GPU, we show that the scatter signal generated by an incident fan beam and recorded by a 125 125 element detector array can be simulated in on the order of a few to tens of minutes (depending on the object extent and complexity). As a point of comparison, simulations performed via CPU-based Monte Carlo tools, such as GEANT4 (i.e., the gold standard), can take up to tens of hours to achieve comparable results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Cyber threat assessment of machine learning driven autonomous control systems of nuclear power plants

We report advanced cyber-attacks against critical infrastructure and the energy sector are becoming more common. With the invention of autonomous control systems (ACS) within advanced nuclear reactor designs, system designers, reactor operators, and regulators must consider cybersecurity during the design and operational phases. This article provides a cyber threat assessment of machine learning (ML)-based digital twinning (DT) technologies in the context of advanced reactor ACS. A cyber–physical testbed was created to emulate nuclear reactor digital instrumentation and controls (I&C) and act as a basis for the ACS. The ACS was designed as two plant-level DTs predicting reactor malfunctions and determining control actions and two component-level DTs responsible for classifying component states and forecasting component inputs and outputs (I/O). Two duplicate ACS designs– one using a traditional ML framework and one using an automated ML (AutoML) framework– were created and tested against cyber-attacks on training data, real-time process data, and ML model architectures to determine their respective qualitative cyber-risk in terms of likelihood and impact. Both frameworks showed similar cyber-resilience against training, real-time, and ML architecture attacks, proving that neither is inherently more secure. Recommended safeguard and security measures are posed to system designers, reactor operators, and regulators to maintain the cybersecurity of ML-based DT technologies such as ACS, prompting a holistic view of shared responsibility for maintaining cyber-secure ML-based systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Combining Radiography and Passive Measurements for Radiological Threat Detection in Cargo

Abstract Radiography is widely understood to provide information complimentary to passive detection: while not directly sensitive to radiological materials, radiography can reveal highly shielded regions which may mask a passive radiological signal. We present a method for combining radiographic and passive data which uses the radiograph to provide an estimate of scatter and attenuation for possible sources. This approach allows quantitative use of radiographic images without relying on image interpretation, and results in a probabilistic description of likely source locations and strengths. We present first results for this method for a simple modeled test case of a cargo container driving through a PVT portal. With this inversion approach, we address criteria for an integrated passive and radiographic screening system and how detection of SNM threats might be improved in such a system.

Combining Radiography and Passive Measurements for↗
DOE OSTI2021

A Localized Cyber Threat Mitigation Approach For Wide Area Control of FACTS

We propose a localized oscillation amplitude monitoring (OAM) method for the mitigation of cyber threats directed at the wide area control (WAC) system used to coordinate control of Flexible AC Transmission Systems (FACTS) for power oscillation damping (POD) of active power flow on inter-area tie lines. The method involves monitoring the inter-area tie line active power oscillation amplitude over a sliding window. We use system instability - inferred from oscillation amplitudes growing instead of damping - as evidence of an indication of a malfunction in the WAC of FACTS, possibly indicative of a cyber attack. Monitoring the presence of such a growth allows us to determine whether any destabilizing behaviors appear after the WAC system engages to control the POD. If the WAC signal increases the oscillation amplitude over time, thereby diminishing the POD performance, the FACTS falls back to POD using local measurements. The proposed method does not require an expansive system-wide view of the network. We simulate replay, control integrity, and timing attacks for a test system and present results that demonstrate the performance of the OAM method for mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2010

Identifying at-risk employees: A behavioral model for predicting potential insider threats

A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. In many of these crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they could be assessed by a person experienced in psychosocial evaluations. We have developed a model using a Bayesian belief network with the help of human resources staff, experienced in evaluating behaviors in staff. We conducted an experiment to assess its agreement with human resources and management professionals, with positive results. If implemented in an operational setting, the model would be part of a set of management tools for employee assessment that can raise an alarm about employees who pose higher insider threat risks. In separate work, we combine this psychosocial model’s assessment with computer workstation behavior to raise the efficacy of recognizing an insider crime in the making.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Global Threat Reduction Initiative Fuel-Thermo-Physical Characterization Project Quality Assurance Plan

The charter of the Fuel Thermo-Physical Characterization Project is to ready Pacific Northwest National Laboratory (PNNL) facilities and processes for the receipt of unirradiated and irradiated low enriched uranium (LEU) molybdenum (U-Mo) fuel element samples, and to perform analysis to support the Global Threat Reduction Initiative conversion program. PNNL’s support for the program will include the establishment of post-irradiation examination processes, including thermo-physical properties, unique to the U.S. Department of Energy laboratories. These processes will ultimately support the submission of the base fuel qualification (BFQ) to the U.S. Nuclear Regulatory Commission (NRC) and revisions to High Performance Research Reactor Safety Analysis Reports to enable conversion from highly enriched uranium to LEU fuel. This quality assurance plan (QAP) provides the quality assurance requirements and processes that support the NRC BFQ. This QAP is designed to be used by project staff, and prescribes the required management control elements that are to be met and how they are implemented. Additional controls are captured in Fuel Thermo-Physical Characterization Project plans, existing procedures, and procedures to be developed that provide supplemental information on how work is conducted on the project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Vulnerabilities in Satellite Communications Underscore Threat to Critical Infrastructure

INL analysts assess critical infrastructure sectors leveraging satellite communications (SATCOM) are likely inadvertently increasing the attack surface caused by inherent vulnerabilities in equipment and communications pathways. A lack of ownership regarding security in SATCOM ecosystems creates pervasive information security risk, and the obfuscation of patching responsibility means the mitigation of publicly and privately disclosed vulnerabilities is difficult to track. With these factors in consideration, INL analysts assess the number of attacks against SATCOM is likely to increase in the next decade as threat actors exploit these vulnerabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Threat Agnostic Virulence Assessment of Pathogens

Virulence assessment of new, emerging, and engineered pathogens is critical to mounting an appropriate response to a biothreat agent. The capacity of the pathogen to colonize human and harm tissues must be characterized to understand pathogenicity pathways and optimize diagnosis and treatment of resulting disease. Respiratory pathogens are of interest because they can have high transmissibility rates, as observed with the SARS-CoV-2 virus, the causative agent of Covid-19. Current technologies are insufficient to assess threats due to their reliance on systems with only one cell type and on sequencing the pathogen. However, it is known that sequence is not an accurate predictor of function, and sequencing can be unreliable for newly emerged or engineered pathogens. An ideal system would consist of relevant epithelial cell types and an assay sensitive enough to detect changes in host responses that do not rely on DNA sequencing. We chose a system consisting of host lung epithelial cells that can be used to assess the virulence of unknown respiratory pathogens. We interrogated pathogens using this model and assess features of pathogenicity. Our objective is to leverage PNNLs strengths in tissue engineering and proteomics capabilities to build a multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) liquid chromatography-tandem mass spectrometry assay for human host cell proteins whose abundance is influenced by infection. These responses can were then assessed for relative virulence using pathogen agnostic signatures. When confronted with a pathogen, cells activate dedicated signaling pathways, typically through phosphorylation of regulatory proteins and downstream activation of host cell networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Psychosocial Modeling of Insider Threat Risk Based on Behavioral and Word Use Analysis

In many insider crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they can be assessed. A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. A complementary Personality Factor modeling approach was developed based on analysis to derive relevant personality characteristics from word use. Several implementations of the psychosocial model were evaluated by comparing their agreement with judgments of human resources and management professionals; the personality factor modeling approach was examined using email samples. If implemented in an operational setting, these models should be part of a set of management tools for employee assessment to identify employees who pose a greater insider threat.

behavioral modeling↗
NASA NTRS2015

Near Earth Asteroid Characteristics for Asteroid Threat Assessment

Information about the physical characteristics of Near Earth Asteroids (NEAs) is needed to model behavior during atmospheric entry, to assess the risk of an impact, and to model possible mitigation techniques. The intrinsic properties of interest to entry and mitigation modelers, however, rarely are directly measureable. Instead we measure other properties and infer the intrinsic physical properties, so determining the complete set of characteristics of interest is far from straightforward. In addition, 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. We will provide an assessment of the current state of knowledge about the physical characteristics of importance to asteroid threat assessment. In addition, an ongoing effort to collate NEA characteristics into a readily accessible database for use by the planetary defense community will be discussed.

Atmospheric↗
DOE OSTI2024

Threats to DERs and Tools to Mitigate Them

As the pace of renewable energy development increases, so does the challenge and opportunity to develop innovative solutions to secure renewable technologies. Four national laboratories National Renewable Energy Laboratory, Sandia National Laboratories, Pacific Northwest National Laboratory, and Idaho National Laboratory are working together to increase cybersecurity maturity levels for solar stakeholders. INL will discuss a DER threat briefing and operator tools and training developed under the Securing Solar for the Grid (S2G) project.

14 SOLAR ENERGY↗
DOE OSTI2010

Combining Traditional Cyber Security Audit Data with Psychosocial Data: Towards Predictive Modeling for Insider Threat Mitigation

The purpose of this chapter is to motivate the combination of traditional cyber security audit data with psychosocial data, so as to move from an insider threat detection stance to one that enables prediction of potential insider presence. Two distinctive aspects of the approach are the objective of predicting or anticipating potential risks and the use of organizational data in addition to cyber data to support the analysis. The chapter describes the challenges of this endeavor and progress in defining a usable set of predictive indicators, developing a framework for integrating the analysis of organizational and cyber security data to yield predictions about possible insider exploits, and developing the knowledge base and reasoning capability of the system. We also outline the types of errors that one expects in a predictive system versus a detection system and discuss how those errors can affect the usefulness of the results.

97 MATHEMATICS AND COMPUTING↗