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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Security Assessment of an LBP16-Protocol-Based Computer Numerical Control Machine

Subtractive manufacturing systems, specifically, computer numerical control machines, have revolutionized the manufacturing industry. Computer numerical control machining is the preferred method for producing finished parts due to its efficiency, speed and suitability for high-volume production. Securing computer numerical control machines is a priority. Compromises or disruptions of these machines can result in significant downtime, loss of productivity and financial loss. This study examines the vulnerabilities and risks associated with computer numerical control machines, in particular, systems utilizing the LBP16 protocol for controller-machine communications. The study reveals that an adversary can execute cyber-physical attacks such as sabotage and denial of service. The potential security threats emphasize the importance of implementing robust security measures to mitigate the cyber risks to computer numerical control machines.

Forihat, Yahya [Virginia Commonwealth University, ↗
DOE OSTI2025

Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx

Facilitating large-scale, cross-institutional collaboration in biomedical machine learning (ML) projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential. Specifically designed for this purpose, this work introduces APPFLx - a low-code, easy-to-use FL framework that enables easy setup, configuration, and running of FL experiments. APPFLx removes administrative boundaries of research organizations and healthcare systems while providing secure end-to-end communication, privacy-preserving functionality, and identity management. Furthermore, it is completely agnostic to the underlying computational infrastructure of participating clients, allowing an instantaneous deployment of this framework into existing computing infrastructures. Experimentally, the utility of APPFLx is demonstrated in two case studies: (1) predicting participant age from electrocardiogram (ECG) waveforms, and (2) detecting COVID-19 disease from chest radiographs. Here, ML models were securely trained across heterogeneous computing resources, including a combination of on-premise high-performance computing and cloud computing facilities. By securely unlocking data from multiple sources for training without directly sharing it, these FL models enhance generalizability and performance compared to centralized training models while ensuring data remains protected. In conclusion, APPFLx demonstrated itself as an easy-to-use framework for accelerating biomedical studies across organizations and healthcare systems on large datasets while maintaining the protection of private medical data.

Biomedical Research↗
DOE OSTI2026

Digital Twin Technology for Safety, Security, and Training in Spent Nuclear Fuel Handling

The increasing complexity of spent nuclear fuel handling requires significant resources to ensure safety, security, and personnel training. As nuclear facilities have continued to advance in scale and technology, the integration of digital tools has become indispensable. Among these tools, digital twins, which are virtual models of physical systems, are emerging as invaluable tools for enhancing safety protocols, security measures, and training in the nuclear sector. These models were conceptualized in the Industry 4.0 revolution. Digital twins can process data from physical systems in real time (by using sensors), include multiple code packages to enable simulations of different physics applications, and even implement artificial intelligence or machine learning techniques for advanced data processing. Despite the advantages that digital twins provide, challenges still exist regarding their widespread implementation. For instance, data used by a digital twin must be accurate to ensure that the digital twin is accurately tuned. Furthermore, if insecure digital twins are targeted by hackers, then they can pose serious risks to the security and safety of nuclear facilities.

Digital twins↗
DOE OSTI2026

Direct Nonlinear Approximation for Security Region Boundary of Integrated Energy Systems: A Polynomial Chaos Expansion Solution

The strong interdependence of electricity, gas, and heating systems can facilitate fault propagation within integrated energy systems (IESs), posing significant challenges to secure operation. This paper proposes a polynomial chaos expansion (PCE)-based approximation method to accurately characterize the IES security region boundary (IES–SRB). By integrating the Karush-Kuhn-Tucker conditions with PCE theory, the IES-SRB approximation problem is reformulated as a set of nonlinear equations concerning the approximation coefficients. Using the Galerkin projection method, these equations are further transformed into a system of projection equations that govern the polynomial approximation coefficients in the IES-SRB approximation. To reduce computational complexity while maintaining high approximation accuracy, a piecewise polynomial approximation method is proposed. Numerical studies on the E39-G20-H6 and E118-G96-H52 IES test systems demonstrate that the proposed method can accurately and effectively construct IES security regions.

Wu, Chenghao [Northeast Electric Power University]↗
DOE OSTI2024

Advanced Reactor Safeguards and Security - Advanced Delay Technologies

As a new generation of reactors is developed, reducing the cost of physical security without impacting the required system effectiveness will help to make new reactors economical. This report discusses several access delay technologies available to help improve the overall effectiveness of the physical security system. These technologies include both passive and active delay elements, as well as guidance on best practices related to security by design principles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Assessment of Physical Security Modeling and Simulation in the Vulnerability Assessment Process

This report provides a comprehensive assessment of physical security modeling and simulation tools available for use in the vulnerability assessment (VA) process for nuclear facilities. It outlines the historical evolution of VA methodologies, emphasizing the transition from traditional layer-based approaches to a more holistic framework that integrates detection probabilities directly into combat simulations. The document details the critical components of the VA process, including the characterization of targets, threats, and protective measures, as well as the development of adversary scenarios that reflect both insider and outsider threats. It highlights the importance of performance assurance programs, emphasizing the need for continuous evaluation and testing of security systems to ensure their effectiveness against evolving threats. Additionally, the report discusses the significance of utilizing accredited modeling and simulation tools in accredited areas to accurately represent adversary actions and the corresponding responses of protective forces. By establishing a systematic approach to VA, this document aims to enhance the overall security posture of nuclear facilities, ensuring compliance with regulatory standards while effectively mitigating risks associated with potential adversarial actions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Microreactor Security-by-Design Recommendations for Domestic and International Deployments

This report outlines methods vendors can use to incorporate security-by-design (SeBD) into their microreactor facility design to support and address security for both U.S. and international deployment. The team developed a hypothetical below-grade microreactor with a physical protection system (PPS) to protect the microreactor against acts of theft and sabotage and evaluated it against two adversary attack scenarios defined by a group of adversary subject matter experts (SMEs). The hypothetical microreactor facility consists of two distinct buildings. The first is the above-grade protected area (PA) entry control point (ECP) building, which houses security personnel responsible for conducting screenings and managing access to the PA. The second building is the reactor building, which features both an above-grade floor and a below-grade floor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Regulatory Considerations for Domestic Reprocessing Facility Physical Security

U.S. advanced non-light-water reactor vendors may pursue collocated on-site reprocessing activities. Therefore, these facilities are likely to possess formula quantities, or Category I quantities, of special nuclear material (SNM) during normal operations. The U.S. Nuclear Regulatory Commission (U.S. NRC) has yet to formally establish a regulatory framework for commercial reprocessing. While Category I requirements would explicitly not apply in this circumstance under current regulatory requirements, regulatory certainty does not exist. A novel framework should be developed to ensure public health and safety while also risk-informing the physical security requirements. This report reviews the relevant background of related rulemaking activities and proposes risk-informed physical protection requirements to satisfy these objectives. Insights from NRC security-related rulemaking activities provide a substantial technical basis to approach potential establishment of physical security requirements for reprocessing facilities. If a licensee can provide justification that the material satisfies a sufficient self-protecting radiation dose threshold, the material may not be subject to theft or diversion requirements and only potential sabotage requirements would apply. Furthermore, if the material can be justified to be moderately dilute, a set of risk-informed requirements could provide adequate protection of public health and safety. A revised performance objective for prevention of theft of moderately dilute Category I SNM may be detection to allow prompt recovery by a local law enforcement agency. However, a significant caveat to the proposed categorization scheme is the unknown integration of radiological sabotage with requirements for the protection against theft. Future licensees should consult with the NRC regarding treatment of this regulatory topic. Additionally, the self-protecting radiation dose threshold (either the existing or a proposed future threshold) would need to be considered. An integrated approach may apply graded potential requirements for protection against the design basis threat of radiological sabotage currently applicable to commercial nuclear power plants and Category I SNM facilities defined within 10 CFR 73.1(a).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A Framework for Building Security into the Design Process

This report presents guidance to support the implementation of security objectives during the design process for nuclear facilities using an organization’s quality management system. The guidance in this document is intended for design vendors and operators of nuclear power facilities. Additionally, this guidance document can be beneficial to regulatory bodies, industry partners, customers, and other stakeholders within the nuclear power market. This report aims to ensure security consequences are identified before designs are completed, which may lead to reduced costs and higher security effectiveness and efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Aggregation and Grid Security Workshop Report

The Aggregation and Grid Security Workshop - held on June 17-18, 2025, National Laboratory of the Rockies (NLR) in Golden, Colorado - brought together approximately 40 external stakeholders from the energy sector, including VPP owner/operators, aggregators, OEMs, utilities, testing & certification labs, trade associations, and cybersecurity vendors. Led by key facilitators, the workshop focused on addressing cybersecurity challenges and enhancing grid resilience for aggregated Distributed Energy Resources (DERs) and Virtual Power Plants (VPPs). The workshop was catalyzed by recognition that traditional, rearward-looking regulatory frameworks are insufficient to keep pace with technological change. There is a "missing understanding" of risk, an "absent security basis" for managing it, and an "untenable responsibility" due to unclear ownership and requirements. The workshop aimed to shift the mindset from reacting to past crises to proactively preparing for emerging threats, fostering forward resilience through risk simulation and collaborative action. This report summarizes the outcomes of the workshop, marking it a significant step toward a secure, reliable and affordable energy future.

14 SOLAR ENERGY↗
DOE OSTI2025

Mitigation for the demolition of the foundation of building 25-3113/3113a, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish the foundation of Building 25-3113/3113A and the adjoining test pad at Test Cell A in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). The foundation of Building 25-3113/3113A (State Historic Preservation Office [SHPO] Resource # B2443) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B2443↗
DOE OSTI2026

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Mitigation for the demolition of building 25-3124,equipment testing laboratory, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-3124 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-3124 (State Historic Preservation Office [SHPO] Resource # B19009) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19009↗
DOE OSTI2025

Mitigation for the demolition of building 25-3153, fire station, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-3153 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-3153 (State Historic Preservation Office [SHPO] Resource # B19004) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19004↗
DOE OSTI2025

Mitigation for the demolition of building 25-4314, radiation services, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-4314 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-4314 (State Historic Preservation Office [SHPO] Resource # B19016) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19016↗
DOE OSTI2025

Mitigation for the demolition of building 25-4838, vehicle maintenance shop, area 25, Nevada national security site, NYE county, Nevada

The purpose of this letter report is to document the mitigation of adverse effects of a proposed undertaking that would demolish Building 25-4838 in Area 25 of the Nevada National Security Site (NNSS) in compliance with the terms of the 2024 Programmatic Agreement among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (NNSS PA). Building 25-4838 (State Historic Preservation Office [SHPO] Resource # B19019) is a contributing element to the Nuclear Rocket Development Station (NRDS) Historic District (SHPO Resource # D424), which has been determined eligible for listing in the National Register of Historic Places (NRHP) under Criteria A, B, C, and D (Reno et al. 2023). The proposed demolition constitutes an adverse effect. The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) consulted with the SHPO on an adverse effect finding for the undertaking and notified the SHPO of its intent to use the standard mitigation in the NNSS PA on December 11, 2024 (Julian to Reed). The SHPO concurred on December 30, 2024 (Reed to Julian). Therefore, NNSA/NFO has prepared mitigation pursuant to the standard mitigation in the NNSS PA Appendix D.I.A for contributing elements to recorded, NRHP-eligible districts.

#B19019↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
DOE OSTI2024

Increasing Diversity in the Field of Radiological Security

This paper will report on a diversity initiative undertaken by the NNSA Office of Radiological Security (ORS), Brookhaven National Laboratory and the Institute of Nuclear Materials Management. This paper will report on the planning associated with inclusion of radiological and nuclear security in the annual meeting program, the process of identifying and selecting individuals who will receive grants to attend the meeting, the expected impact of the INMM/ORS diversity initiative on the nuclear security community, and lessons learned.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗