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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hands-On, Heads-Up: Blending Cyber T&E with Data Science-Driven Training in Jupyter Notebooks

In an era of increasingly sophisticated threats to critical infrastructure, cybersecurity professionals must be more than just aware; they must be immersed, agile, and equipped to operate in environments where failure is not an option. Nowhere is this truer than in the nuclear sector, where cyber-physical systems, regulatory scrutiny, and insider threat potential demand a new generation of hands-on, technically fluent defenders. This paper presents a unified training approach that integrates Cybersecurity Test and Evaluation (T&E) with data science techniques using Jupyter Notebooks as the interactive lab environment. The program centers on a modular, scenario-driven curriculum designed to build not just knowledge but practical capability in the assessment and defense of radiation detection systems, firmware interfaces, and operational security postures.

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

Dante

SAND2022-12905 O Dante is a physical security simulation package used in evaluating protective staffing and physical security elements against adversarial threats. Dante simulates force-on-force scenarios in a batch Monte Carlo process. Analysts use the included Scenario Editor to define the scenarios for their site and then execute and analyze the results using the Batch Manager tool. Dante provides insight into how well a security system performs against threats and lets analysts mine the results for key indicators of system performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, Brian↗
DOE OSTI2022

Reinforcement Learning for feedback-enabled cyber resilience

The rapid growth in the number of devices and their connectivity has enlarged the attack surface and made cyber systems more vulnerable. As attackers become increasingly sophisticated and resourceful, mere reliance on traditional cyber protection, such as intrusion detection, firewalls, and encryption, is insufficient to secure the cyber systems. Cyber resilience provides a new security paradigm that complements inadequate protection with resilience mechanisms. A Cyber-Resilient Mechanism (CRM) adapts to the known or zero-day threats and uncertainties in real-time and strategically responds to them to maintain the critical functions of the cyber systems in the event of successful attacks. Feedback architectures play a pivotal role in enabling the online sensing, reasoning, and actuation process of the CRM. Reinforcement Learning (RL) is an important gathering of algorithms that epitomize the feedback architectures for cyber resilience. It allows the CRM to provide dynamic and sequential responses to attacks with limited or without prior knowledge of the environment and the attacker. In this work, we review the literature on RL for cyber resilience and discuss the cyber-resilient defenses against three major types of vulnerabilities, i.e., posture-related, information-related, and human-related vulnerabilities. Here we introduce moving target defense, defensive cyber deception, and assistive human security technologies as three application domains of CRMs to elaborate on their designs. The RL algorithms also have vulnerabilities themselves. We explain the major vulnerabilities of RL and present develop several attack models where the attacker target the information exchanged between the environment and the agent: the rewards, the state observations, and the action commands. We show that the attacker can trick the RL agent into learning a nefarious policy with minimum attacking effort. The paper introduces several defense methods to secure the RL-enabled systems from these attacks. However, there is still a lack of works that focuses on the defensive mechanisms for RL-enabled systems. Last but not least, we discuss the future challenges of RL for cyber security and resilience and emerging applications of RL-based CRMs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Cyber-Resilience Risk Management Architecture for Distributed Wind

Distributed wind is an electric energy resource segment with strong potential to be deployed in many applications, but special consideration of resilience and cybersecurity is needed to address the unique conditions associated with distributed wind. Distributed wind is a strong candidate to help meet renewable energy and carbon-free energy goals. However, care must be taken as more systems are installed to ensure that the systems are reliable, resilient, and secure. The physical and communications requirements for distributed wind mean that there are unique cybersecurity considerations, but there is little to no existing guidance on best practices for cybersecurity risk management for distributed wind systems specifically. This research develops an architecture for the consideration of cyber risks associated with distributed wind systems. The architecture takes into account the configurations, challenges, and standards for distributed wind to create a risk-focused perspective that considers of threats, vulnerabilities, and consequences, with special emphasis on what sets distributed wind systems apart from other distributed energy resources (DER). We discuss common distributed wind architectures and how they are interconnected to larger power systems. Because cybersecurity cannot exist independently, the cyber-resilience architecture must consider the system holistically. Finally, we discuss the implementation of a risk assessment process that uses the cyber-resilience framework to address challenges specific to distributed wind.

17 WIND ENERGY↗
DOE OSTI2019

Characterizing Vulnerabilities Associated with Connected Lighting: Exploring Authorization Protocols

Cities are upgrading their infrastructure and converting traditional indoor and outdoor luminaires to Connected Lighting Systems equipped with sensors in an aggressive effort to reduce energy consumption, increase sustainability, and improve the quality of life. When you take something seemingly benign like a lighting system and connect it to the internet, if improperly secured a potential attack vector for hackers is created. Hackers could then access sensitive information, pivot into other networks, shut down services, or enslave devices to do their bidding. In attempt to close this attack vector and secure these systems, this paper extends previous work that investigated, compared and contrasted authentication vulnerabilities in Connected Lighting Systems that identified the need for additional testing and improved test method documentation. One additional authentication test and four new authorization tests were developed utilizing the Open Web Application Security Project (OWASP) as a test development and documentation guide. The new tests were integrated with the previous work to develop an updated test method with a focus on describing test procedures to make them easy to understand and repeat. In addition, a first Connected Lighting System use case was established to begin developing threat profiles that will aid in the identification of vulnerabilities whose focus areas extend beyond authentication and authorization. This use case describes the generation and flow of CLS data which assists in specifying methods to harden CLSs from outside interference and exploitation that can be implemented immediately on existing CLSs and as new products come to market.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Inventory and Probabilistic Function of Natural Hazards in the United States: July 19, 2018 - September 18, 2018

The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a standardized risk assessment process that considers the location-specific vulnerabilities and threats (climate-related as well as human-caused) at a site to generate a ranked list of organizational risks and associated mitigation options for reducing those risks. To support this effort, the Southern Climate Impacts Planning Program (SCIPP), a National Oceanic and Atmospheric (NOAA) Regional Integrated Sciences and Assessments (RISA) team, was selected to provide climate science expertise to develop a comprehensive inventory and probabilistic function of natural hazards (e.g., hurricanes, tornadoes, flooding, and sea level rise) for the entire United States by region. The inventory of climate-related hazards and the associated likelihood scores are incorporated into a companion risk assessment tool enabling standardized comparisons of risk at sites across the country.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Securing Distributed Energy Resource Integration

The penetration of distributed energy resources (DER) is growing at much higher rates than predicted 20 years ago. Far from being used only in residential settings, DER are now installed on distribution and transmission circuits. In this position, they do not have the same properties as traditional generators and are more flexible in many cases. The growing penetration and range of uses for DER motivate the need to reliably and safely integrate them into the grid. Operators must be able to rely on them not only for normal operation, but also during abnormal conditions like black starts or adverse cyber scenarios. To that end, we study the communications, device interfaces, and potential consequences of DER operation under abnormal and adversarial conditions. The weaknesses of communications networks are studied based on the industrial protocols used, and the benefits of security features are examined. The device interfaces are found to be vulnerable to attack based on the requirements in the IEEE-1547 standard for DER interconnection and interoperability, which is expected to be adopted in the next ten years. In addition to exploring the requirements of the standard, we show that these vulnerabilities and others do exist and can be used maliciously in a modern storage system DER. Consequences of these vulnerabilities range from exacerbated grid instability, to simultaneous loss of large portions of DER penetration, to physical damage to inverters or DER themselves and other sensitive equipment. We tie these outcomes to specific attacker actions in an effort to give operators a better threat intelligence view that allows them to prioritize mitigations. Finally, we discuss mitigations that could prevent many of the adversarial scenarios described. Some solutions can be added to existing infrastructure, while others may require longer term planning for grid modernization with consideration for security.

25 ENERGY STORAGE↗
DOE OSTI2021

Neighborhood Keeper

Neighborhood Keeper is a collective defense and community-wide visibility solution that provides a more effective industrial cyber defense by sharing threat intelligence at machine-speed across industries and geographic regions.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Attack Surface of Wind Energy Technologies in the United States

Low cost, reliable electrical energy production from wind relies upon automation and control systems, arguably more so than traditional thermal generation. These same systems, however, can serve as the target of adversaries’ cyber-attacks. Idaho National Laboratory (INL), at the request of the Department of Energy’s (DOE’s) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) and Energy Efficiency and Renewable Energy’s (EERE’s) Wind Energy Technologies Office (WETO), evaluated a generalized wind plant architecture to understand the classes of potential threat actors and the vectors that could enable a cyber-attack. This evaluation explores the attack surface of a representative wind plant, identifying potential methods and vectors that an adversary could leverage to conduct a cyber-attack. Included in this assessment are some recommended mitigations and approaches. Each recommendation requires a full security evaluation, cost/benefit analysis, and risk analysis by each owner and operator.

17 WIND ENERGY↗
DOE OSTI2022

Mental Models for Managing Grid Cybersecurity Risk - ARC Industry Forum, Cybersecurity and Energy Transition

A proper mental model of the concepts of cyber risk and its components of threat and exploitability and consequence is necessary to allocate limited resources to different security activities, especially when considered alongside reliability and regulatory and economic risks. Understanding the consequence and frequency different risks are realized also helps align the right mitigations to the right risks. Cyber-informed engineering (CIE) is an emerging method to “engineer out” cyber risk across product and system lifecycles, and INL has a portfolio of programs operationalizing CIE’s principles for the energy sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Assurance by Design for Cyber Physical Data-Driven Systems

Currently, Cyber Physical Data-Driven Systems (CPDDS) employ machine learning for the classification, data fusion, and control of our nation’s infrastructure, such as the power grid, transportation networks (e.g., fuel distribution, air traffic control), and DoD long-duration collaborative autonomous platforms including unmanned underwater, ground, surface, space, and aerial systems. Many CPDDSs are system-of-systems that should be designed to communicate over disadvantaged networks. It is important to assure that the CPDDSs are resilient against physical and cyber threats by design. Additionally, their design should tolerate misclassification errors resulting from natural and/or adversarial distribution shifts within their data driven components. The all-domain nature of the problem of assuring the design of CPDDSs requires a multi-disciplinary perspective as outlined in this chapter.

Chikkagoudar, Satish↗
DOE OSTI2023

Radiation biology workforce in the United States

In recent decades, the principal goals of participants in the field of radiation biologists have included defining dose thresholds for cancer and non-cancer endpoints to be used by regulators, clinicians and industry, as well as informing on best practice radiation utilization and protection applications. Importantly, much of this work has required an intimate relationship between “bench” radiation biology scientists and their target audiences (such as physicists, medical practitioners and epidemiologists) in order to ensure that the requisite gaps in knowledge are adequately addressed. However, despite the growing risk for public exposure to higher-than-background levels of radiation, e.g. from long-distance travel, the increasing use of ionizing radiation during medical procedures, the threat from geopolitical instability, and so forth, there has been a dramatic decline in the number of qualified radiation biologists in the U.S. Contributing factors are thought to include the loss of applicable training programs, loss of jobs, and declining opportunities for advancement. This report was undertaken in order to begin addressing this situation since inaction may threaten the viability of radiation biology as a scientific discipline.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Trace Adsorptive Removal of PFAS from Water by Optimizing the UiO‐66 MOF Interface

Abstract The confluence of pervasiveness, bioaccumulation, and toxicity in freshwater contaminants presents an environmental threat second to none. Exemplifying this trifecta, per‐ and polyfluoroalkyl substances (PFAS) present an alarming hazard among the emerging contaminants. State‐of‐the‐art PFAS adsorbents used in drinking water treatment, namely, activated carbons and ion‐exchange resins, are handicapped by low adsorption capacity, competitive adsorption, and/or slow kinetics. To overcome these shortcomings, metal–organic frameworks (MOFs) with tailored pore size, surface, and pore chemistry are promising alternatives. Thanks to the compositional modularity of MOFs and polymer–MOF composites, herein we report on a series of water‐stable zirconium carboxylate MOFs and their low‐cost polymer‐grafted composites as C 8 –PFAS adsorbents with benchmark kinetics and “parts per billion” removal efficiencies. Bespoke insights into the structure–function relationships of PFAS adsorbents are obtained by leveraging interfacial design principles on solid sorbents, creating a synergy between the extrinsic particle surfaces and intrinsic molecular building blocks.

Ilić, Nebojša↗
DOE OSTI2021

Neutralizing Antibodies to SARS-CoV-2 Selected from a Human Antibody Library Constructed Decades Ago

Combinatorial antibody libraries not only effectively reduce antibody discovery to a numbers game, but enable documentation of the history of antibody responses in an individual. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has prompted a wider application of this technology to meet the public health challenge of pandemic threats in the modern era. Herein, a combinatorial human antibody library constructed 20 years before the coronavirus disease 2019 (COVID-19) pandemic is used to discover three highly potent antibodies that selectively bind SARS-CoV-2 spike protein and neutralize authentic SARS-CoV-2 virus. Compared to neutralizing antibodies from COVID-19 patients with generally low somatic hypermutation (SHM), these three antibodies contain over 13–22 SHMs, many of which are involved in specific interactions in their crystal structures with SARS-CoV-2 spike receptor binding domain. The identification of these somatically mutated antibodies in a pre-pandemic library raises intriguing questions about the origin and evolution of these antibodies with respect to their reactivity with SARS-CoV-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Bio‐Inspired Cascade Photocatalysis on Fe Single‐Atom Carbon Nitride Upcycles Plastic Wastes for Effective Acetic Acid Production

Plastic imposes a critical threat to the environment, ecosystems, and human health because of the low utilization efficiency of plastics. Here, we demonstrate a sustainable, highly efficient cascade photocatalysis for upcycle plastics to value-added acetic acid using Fe single-atom catalysts (Fe@C 3 N 4 SAC) at ambient conditions. Inspired by Phanerochaete chrysosporium microbial, the defective Fe@C 3 N 4 SAC acts as a bifunctional cascade photocatalyst for both Fenton-like and CO 2 reduction reactions. During the reaction, hydroxyl radicals (*OH) form and subsequently oxidize plastics into CO 2 intermediates. These CO 2 intermediates are then photo-reduced to CH 3 COOH on the same catalyst via cascade photocatalysis. The mechanism is confirmed by in situ multimodal microscopy and spectroscopies, with density functional theory calculations. A state-of-art CH 3 COOH yield of 63.8 mg h −1 gcat −1 from PVC, 12.7 mg h −1 gcat −1 from PE, 5.4 mg h −1 gcat −1 from PET, and 5.3 mg h −1 gcat −1 from PP are directly obtained under AM1.5G solar irradiation and further validated under real sunlight (≈0.6 sun), achieving 5.6 mg h −1 gcat −1 from PET, using low-cost Fe@C 3 N 4 SAC in a sealed reactor by enhancing the photon transport and utilization efficiency. The techno-economic analysis shows it is promising to practically mitigate plastic based on broader social welfare assessments.

cascade photocatalysis↗
DOE OSTI2023

Porous Materials for Water Purification

Abstract Water pollution is a growing threat to humanity due to the pervasiveness of contaminants in water bodies. Significant efforts have been made to separate these hazardous components to purify polluted water through various methods. However, conventional remediation methods suffer from limitations such as low uptake capacity or selectivity, and current water quality standards cannot be met. Recently, advanced porous materials (APMs) have shown promise in improved segregation of contaminants compared to traditional porous materials in uptake capacity and selectivity. These materials feature merits of high surface area and versatile functionality, rendering them ideal platforms for the design of novel adsorbents. This Review summarizes the development and employment of APMs in a variety of water treatments accompanied by assessments of task‐specific adsorption performance. Finally, we discuss our perspectives on future opportunities for APMs in water purification.

Song, Yanpei↗
DOE OSTI2022

Porous Materials for Water Purification

Water pollution is a growing threat to humanity due to the pervasiveness of contaminants in water bodies. Significant efforts have been made to separate these hazardous components to purify polluted water through various methods. However, conventional remediation methods suffer from limitations such as low uptake capacity or selectivity, and current water quality standards cannot be met. Recently, advanced porous materials (APMs) have shown promise in improved segregation of contaminants compared to traditional porous materials in uptake capacity and selectivity. These materials feature merits of high surface area and versatile functionality, rendering them ideal platforms for the design of novel adsorbents. Here, this Review summarizes the development and employment of APMs in a variety of water treatments accompanied by assessments of task-specific adsorption performance. Finally, we discuss our perspectives on future opportunities for APMs in water purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗