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At least 73 records · Page 4

ILLICIT TRANSIT INTERDICTION GLOBAL ANALYSIS

This study aims to enhance the security of radioactive materials during transport by analyzing commonalities in cargo thefts conducted by non-state groups such as thieves and terrorists. This research focuses on identifying patterns and trends in the methods used to steal high-value cargo, with the goal of applying these insights to improve transport security of radioactive materials. Key questions addressed include the frequency of specific tools, techniques, and insider involvement in thefts, as well as the use of weapons, electronic jamming equipment, and specialized tools. Findings will inform security design improvements and industry practices to mitigate vulnerabilities. The study involves a comprehensive review of literature and case studies, utilizing data sources from 2018 to 2023. Articles will be selected based on their relevance to thefts of valuable cargo in transit, with a focus on incidents involving non-state actors. The methodology will include statistical and inferential analysis to identify trends, with results visualized through pie charts, frequency analyses, and terrain maps. The discussion will highlight the implications of findings and provide actionable recommendations for strengthening security measures. Limitations such as data availability and reporting inconsistencies will be acknowledged. Suggestions for future improvements will be constructed using existing case studies and expert feedback. The study’s outcomes aim to raise awareness within the industry, inform policy decisions, and enhance security protocols for radioactive material transport. Metrics for impact include the potential publication of findings, presentations at conferences to raise awareness, and the subsequent actions taken by stakeholders based on the research. By identifying trends and vulnerabilities and suggesting improvements, this research contributes to preventing the illicit use of nuclear and radiological materials.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗

A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings

In recent years, there has been a growing trend toward the development of smart buildings that rely on cyber-physical systems (CPS) to optimize occupant comfort, safety, and energy efficiency. To ensure the reliable and efficient operation of CPS with designed control strategies, it is important to evaluate their performance under various scenarios before deploying them in the real world. This is where a Hardware-in-the-loop (HIL) testbed designed for studying sensor and control-related studies in smart buildings can be highly valuable. With the growing threat of cyber-attacks and physical faults targeting smart buildings, it is essential to ensure the security of building operations. A HIL testbed can emulate cyber-attack and physical fault scenarios, allowing researchers to develop and test threat detection and mitigation algorithms. This enables researchers to identify potential issues and optimize the algorithms in a safe and controlled environment before they are deployed in real-world settings, reducing the risk of failures that can negatively impact occupant comfort, safety, and energy efficiency. Therefore, this paper developed a HIL testbed designed for cyber-physical energy systems (e.g. buildings automation system (BAS)) in smart commercial buildings. The HIL testbed is comprised of a real-time building and Heating, Ventilation, and Air-Conditioning (HVAC) emulator using Modelica-based dynamic models, a set of BAS controllers, and a BAS computer server. The data generation capability of the HIL testbed is demonstrated by tracking normal and faulty operating data in the BAS, as well as monitoring detailed network traffic in the local BAS network. Here, this study further demonstrates the HIL testbed’s capability by conducting case studies on real-time physical fault and cyber-attack experiments using a Department of Energy (DOE) prototype commercial building. It is anticipated that the fully functional HIL testbed will be utilized for a variety of sensor and control-related studies, including but not limited to testing, developing, validating of different HVAC control strategies, fault detection & diagnosis, energy monitoring and analysis, cyber security study, etc.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

IEEE PES GM Poster - Cyber-Informed Engineering Approach to Mitigating BESS Supply Chain Concerns

Battery energy storage systems (BESS) are increasingly important to meet the needs of grid resilience and reliability. BESS provide critical grid services, maintaining stability of the grid with increased variable conditions. However, there are significant geopolitical and security concerns regarding their operation in critical infrastructure, due to lack of a domestic supply chain and prevalence of foreign entity of concern (FEOC) components in BESS and associated inverter-based resources. The supply chain challenge is dually exacerbated by a lack of alternative suppliers who can meet the economic targets for energy delivery and a potentially adversarial supply chain. Solutions are needed to secure components, addressing mixed layers of risk and engineering controls. This paper presents a specific application of Cyber-Informed Engineering (CIE) principles for BESS and recommends an alternative strategy to blocking the supply chain, ensuring that grid modernization targets can be met despite lack of a validated or secure supply chain. This study focuses on the United State (U.S.) use case, but the process can be applied globally to address supply chain security challenges. CIE practices represent the next step in functional assurance and risk mitigation, ensuring optimal resource allocation and enhancing security measures to safeguard the future of energy in the U.S. and beyond.

25 - ENERGY STORAGE↗

Power Supply Options for the Marpi Landfill, Saipan: Addendum to 2023 Feasibility Study

The Marpi Landfill (Marpi or the landfill), located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by an on-site diesel generator that only operates when the landfill is open and staffed. The CNMI Office of Planning and Development (OPD) aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location and to increase sustainable energy consumption within the CNMI. Pacific Northwest National Laboratory (PNNL) authored a feasibility study in 2023 that explores alternative power supply options for the landfill. This feasibility study (hereafter referred to as Phase I of this study) culminated in a report named “Power Supply Options for the Marpi Landfill, Saipan.” In Phase I, the project team investigated and prioritized seven different power supply scenarios (Table ES-1) for the landfill according to Solid Waste (SW) Taskforce priorities. The project team found that Scenario 4 (100 kW of solar photovoltaic [PV] generation, a 75 kW/300 kWh battery energy storage system [BESS], and 160 kW of diesel generation) ranked highest. Following the Phase I feasibility study, the SW Taskforce secured additional funding for PNNL to assess additional considerations regarding power supply options for Marpi. The purpose of Phase II of this study is to investigate these additional considerations, as compiled in this addendum. Some of the findings compiled here replace findings from the original report. The project team evaluated additional considerations regarding power supply options for the landfill, including modified operations to account for 24/7 power supply, electrified landfill equipment, new and replacement distribution line costs, and the social cost of carbon.

14 SOLAR ENERGY↗

Nuclear Security Risks for HALEU Fuels

There is growing interest in high-assay low-enriched uranium (HALEU) for use in advanced nuclear reactors as a high-energy fuel source. The primary objectives of this report are to identify the security risks that directly result from HALEU and to identify the gaps and challenges it presents from a theft and sabotage perspective. This study focuses on HALEU security risks for the front end of the fuel cycle and includes a review of the supply chain, fuel fabrication, and transport for terrestrial reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DGaaS: GPU as a Service on Distributed Computing System

In the rapidly evolving landscape of scientific computing, Graphics Processing Units (GPUs) have become indispensable for their unparalleled ability to handle parallel tasks in complex calculations, simulations, and data analysis. Their utility is further magnified in machine learning and AI applications, where they significantly accelerate model training and predictive analytics. Within this context, the Triton Inference Server emerges as a pivotal open-source tool, specializing in AI inferencing and optimizing GPU utilization across various platforms and frameworks. This paper presents an in-depth study on distributed High Throughput Computing (HTC), specifically focusing on the HTCondor framework and its resource provisioning tools, GlideinWMS and HEPCloud. These systems enable large-scale scientific experiments like CMS and DUNE to efficiently access and utilize vast computational resources. The paper explores the core architectural components of GlideinWMS, including jobs, user pools, and worker nodes, and discusses their integration with GPUs and the Triton server. The primary aim of this research is to develop a solution that optimizes GPU utilization by leveraging Glideins and containers. This approach allows computational jobs, particularly those involving AI models, to use GPUs only when essential, thereby facilitating efficient sharing of limited GPU resources. To validate this architecture, the study conducted three key tests involving custom scripts, container-based servers, and Triton server deployments. However, the study faces challenges, notably in locating the Triton server and ensuring secure remote access. To address these issues, future work will focus on developing a proxy mechanism and enhancing security protocols. In conclusion, this study offers a comprehensive roadmap for effective and efficient GPU utilization in distributed High Throughput Computing. It aims to contribute significantly to the scientific community by solving pressing problems and implementing robust solutions in collaboration with the GlideinWMS and HEPCloud teams. The research sets the stage for a more efficient, scalable, and cost-effective paradigm in scientific computing.

97 MATHEMATICS AND COMPUTING↗

Countering Weapons of Mass Destruction Office (CWMD) Data Categorization Study: Chemical, Biological, Radiological, and Nuclear (CBRN) Detection Device Data

Pacific Northwest National Laboratory (PNNL) seeks to address critical questions related to chemical, biological, radiological, and nuclear (CBRN) detection devices. This research aims to enhance the security and understanding of these devices by investigating various aspects of their identification, communication, and functionality. The primary focus is on network security, malware detection, device identification, and intelligence gathering. CBRN data can be categorized in various ways depending on the purpose of CBRN detection devices and the specific context of the applications for analysis. Criteria that can be used to assist in this effort include but are not limited to data type, data protocol, source/destination, application, time, security, and content. This study will inform additional paths for data classification, data profiling, data mapping, and data modeling. This will help the Countering Weapons of Mass Destruction Office (CWMD) better understand their data and make informed decisions based on the insights gained from this study and their application. The CBRN Data Categorization study will include the identification of 5–10 different CBRN detection devices with unique characteristics for assessing and analyzing the data that is being produced by and transmitted from these devices.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

STEM Professional Development Program for Nuclear Security Science and Technology Consortium

This oral presentation captures the technical and developmental aspect of the program in support of UNLV. The goal of this project is to develop a steady pipeline of STEM educated professionals in area of national and international nuclear security. The goal is to train university students at NNSS laboratories in studies motivated by global nuclear security topics ranging from nuclear emergency response and management to physics experiments for stockpile stewardship program.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Combinatoric Researchers at Sandia National Laboratories: An ethnographic study

Combinatorial research, the incorporation of multiple domains in a unified research agenda, is a strong contributor to the growing corpus of scientific knowledge and technological advancements worldwide. In 2019, a study team at Sandia National Laboratories (Sandia, the Labs) used a systems approach to understand if and how combinatorial research agendas were playing out at Sandia, one of America’s premiere national security research venues. The study team used the data collection effort described in this report to ground the discussion of the broad social environment and particular organizational environments within which combinatorial research agendas are developed, as described in the full study. The team interviewed twenty-five staff members engaged in combinatorial research at Sandia in New Mexico and California during the months of June – September 2019. Analysis of this corpus of ethnographic data, combined with knowledge drawn from relevant literature, concluded that there is an individual type who would be most likely to engage in combinatoric research, described by both demographic and psychographic components. This type demonstrates both intellectual depth and the curiosity which leads to breadth. The analysis also showed that Sandia as an organization and as perceived by the respondents, set up tension for the combinatorial researcher. While Sandia was generally agnostic towards combinatorial research, that agnostic posture depended on whether the researcher was able to fulfill all her customer obligations – obligations that are structured primarily in transactional relationships with customers with relatively short time horizons. This report concludes with suggestions for additional research in the ethnographic domain.

99 GENERAL AND MISCELLANEOUS↗

Experimental Setup for Grid Control Device Software Updates in Supply Chain Cyber-Security

Supply chain cyberattacks that exploit insecure third-party software are a growing concern for the security of the electric power grid. These attacks seek to deploy malicious software in grid control devices during the fabrication, shipment, installation, and maintenance stages, or as part of routine software updates. Malicious software on grid control devices may inject bad data or execute bad commands, which can cause blackouts and damage power equipment. This paper describes an experimental setup to simulate the software update process of a commercial power relay as part of a hardware-in-the-loop simulation for grid supply chain cyber-security assessment. The laboratory setup was successfully utilized to study three supply chain cyber-security use cases.

Keller, Joseph↗

Study of Applications of Radiological Data Fusion for Nuclear Security and Non-proliferation Applications

This report describes the radiological Scene Data Fusion (SDF) technology and the potential to apply the SDF technology to a variety of problems related to nuclear non-proliferation, radiological security, and other missions related to the national nuclear security agency and the US government, more broadly. The application space was conceived by both the authors of this report and the many scientists and stakeholders they interviewed. In order to successfully apply the SDF technology to the various applications, further research and development is often necessary and those R&D steps are also outlined herein.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Attacking the IEC-61131 Logic Engine in Programmable Logic Controllers in Industrial Control Systems

In industrial control systems (ICS), programmable logic controllers (PLCs) directly monitor and control a physical process such as nuclear power plants, gas pipelines, and water treatment. They are equipped with a control logic written in IEC-61131 languages (e.g., ladder logic and structured text) that defines how a PLC should control a physical process. A PLC's control logic is a usual target of a cyberattack to sabotage a physical process. For instance, Stuxnet targets a control logic of a Siemens S7-300 PLC to damage a nuclear facility's centrifuges. The existing attacks in the literature generally focus only on injecting malicious control logic into a PLC. This paper presents a new dimension of control logic attacks that target the control logic engine (responsible for running a control logic) of a PLC. It demonstrates that a cyberattack can disable the control logic engine successfully by exploiting inherent PLC features such as program mode and starting/stopping engine. We develop two novel case studies on control logic engine attacks by employing the MITRE ATT\&CK knowledge base on the real-world PLCs used in industry settings, i.e., 1) Schweitzer Engineering Laboratory (SEL)'s Real-Time Automation Controller (SEL-3505 RTAC) equipped with security features such as encrypted traffic and device-level access control, and 2) traditional PLCs, i.e., Schneider Electric's Modicon M221, Allen-Bradley's MicroLogix 1400 and 1100 that do not have security features. The case studies present the internals of the logic engine attacks and facilitate the ICS research community and industry to understand the attack vectors on the control logic engine. We evaluate the effectiveness of the control engine attacks on a power substation, a 4-floor elevator, and a conveyor belt to demonstrate their real-world impact of halting a physical process.

Ali qasim, Syed↗

Integrating PCTRAN with AI-Driven Host-Intrusion Detection and Secured Container Systems for Advanced Malware Analysis (Summer Internship Report)

This study presents a solution for enhancing the security of the Personal Computer Transient Analyzer (PCTRAN) PC-based Nuclear Power Plant Simulator by integrating the software with an artificial intelligence (AI)-driven host-intrusion detection system (HIDS), in addition to a secured container system, for malware analysis. PCTRAN is a Windows XP-based software package that has the ability to simulate a variety of accident and transient conditions for nuclear power plants (NPPs). It offers a high-resolution replica of the Nuclear Steam Supply System (NSSS) and displays the status of important parameters allowing for operator interaction. By including AI-driven HIDS for the NSSS, the framework can identify security threats in real-time, ensuring the integrity of the nuclear simulation environment. Additionally, the secured container system offers the ability to isolate and analyze malware, preventing potential threats from affecting core systems. The integration process involves extensive testing and validation in order to ensure accuracy, reliability, and compliance with security policies. This framework sets a new precedent for secure simulation and training in NPP operations, and offers insight for future advancements in cybersecurity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗