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At least 685 records · Page 38

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↗

Cyber-Informed Engineering Case Study of an Integrated Hydrogen Generation Plant

Strategies for securing digital instrumentation and control (I&C) systems within the nuclear industry are provided by multiple standards and guidance documents. However, since selection and use of security controls outlined in these documents are frequently only considered during or after installation, there are often limitations on their use, such as technological constraints related to design or operation. Furthermore, alternative controls intended to provide the same or similar security countermeasure as the primary control may also be infeasible at these stages, leaving the I&C system vulnerable to cyber-attacks. The limitations associated with ‘bolting on’ security controls late in the systems engineering lifecycle can be reduced by integrating Cyber-Informed Engineering (CIE) into the process. This paper evaluates the use of CIE during the high-level design stage of a hydrogen generation project where heat and electricity are provided by a nuclear power plant. Applying CIE to this project highlighted potential cyber vulnerabilities of the initial design, leading to recommendations for process flow and I&C system design modifications to reduce, and at times eliminate, the risk from both deliberate and unintentional cyber incidents.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Capabilities for Water Sector Infrastructure Resilience - Prioritizing RD&D in a Target Rich, Resource Poor Sector

WSTB & Water Sector Security Program Expansion Objective: Incubate and shepherd a public-private consortium of joint seal US government sponsors and industry stakeholders to build out industrial control system (ICS) and operational technology (OT) architecture of the Idaho National Laboratory (INL) Water Security Test Bed (WSTB) asset to enable research, testing, and cyber workforce training related to evolving cyber-physical and physical vulnerabilities and threats in the water sector.

99 - GENERAL AND MISCELLANEOUS↗

Deep Learning-Based Adaptive Remedial Action Scheme with Security Margin for Renewable-Dominated Power Grids

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Field Programmable Gate Array-Based Reactor Protection Systems and Potential for Inclusion of Secure Elements to Improve Cybersecurity

For acceptable implementations of technologies like wireless communications, remote monitoring, etc., strong mitigations must be developed and evaluated to ensure that new attack pathways do not increase risk for Advanced Reactors. Secure Elements can be adopted and adapted for this purpose based on tamper resistance and cryptographic abilities, but research must be done to properly integrate into critical components such as FPGA-based Important to Safety systems in conjunction with current and future regulations on cyber security features in Advanced Reactors. Typically, the integration of a Secure Element happens during the POST and UEFI boot of a computing platform, performed by the Operating System, which is not possible with FPGAs because they do not include these firmware components. Work must be done to identify a reliable and secure method for integration in FPGA-based systems which lack Operating Systems and therefore complex boot procedures, system calls, etc.

97 MATHEMATICS AND COMPUTING↗

Field Programmable Gate Array-Based Reactor Protection Systems and Potential for Inclusion of Secure Elements to Improve Cybersecurity

For acceptable implementations of technologies like wireless communications, remote monitoring, etc., strong mitigations must be developed and evaluated to ensure that new attack pathways do not increase risk for Advanced Reactors. Secure Elements can be adopted and adapted for this purpose based on tamper resistance and cryptographic abilities, but research must be done to properly integrate into critical components such as FPGA-based Important to Safety systems in conjunction with current and future regulations on cyber security features in Advanced Reactors. Typically, the integration of a Secure Element happens during the POST and UEFI boot of a computing platform, performed by the Operating System, which is not possible with FPGAs because they do not include these firmware components. Work must be done to identify a reliable and secure method for integration in FPGA-based systems which lack Operating Systems and therefore complex boot procedures, system calls, etc.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Data for training and testing radiation detection algorithms in an urban environment

The detection, identification, and localization of illicit nuclear materials in urban environments is of utmost importance for national security. Most often, the process of performing these operations consists of a team of trained individuals equipped with radiation detection devices that have built-in algorithms to alert the user to the presence nuclear material and, if possible, to identify the type of nuclear material present. To encourage the development of new detection, radioisotope identification, and source localization algorithms, a dataset consisting of realistic Monte Carlo-simulated radiation detection data from a 2 in. × 4 in. × 16 in. NaI(Tl) scintillation detector moving through a simulated urban environment based on Knoxville, Tennessee, was developed and made public in the form of a Topcoder competition. The methodology used to create this dataset has been verified using experimental data collected at the Fort Indiantown Gap National Guard facility. Realistic signals from special nuclear material and industrial and medical sources are included in the data for developing and testing algorithms in a dynamic real-world background.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Deception-Based Cyber Attacks on Hierarchical Control Systems using Domain-Aware Koopman Learning

Industrial control systems are subject to cyber attacks that produce physical consequences. These attacks can be both hard to detect and protracted. Here, we focus on deception-based sensor bias attacks made against a hierarchical control system where the attacker attempts to be stealthy. We develop a a data-driven, optimization-based attacker model and use the Koopman operator to represent the system dynamics in a domain-aware and computationally efficient manner. Using this model, we compute several different attacks against a high-fidelity commercial building emulator and compare the impacts of those attacks to each other. Finally, we discuss some computational considerations and identify avenues for future research.

koopman operator, Cyber-Physical Security, machine↗

Sensor and Actuator Attacks on Hierarchical Control Systems with Domain-Aware Operator Theory

Cyber-Physical Systems (CPSs) provide opportunities for cyber attacks to have physical impacts. Advanced Persistent Threats (APTs) are a subclass of cyber threats that act stealthily to avoid detection and enable long-term attacks. Here, we build on our past work in APT modelling to combine deception-based sensor bias attacks and direct actuator manipulations in attacks against a hierarchical control system. That past work used the Koopman operator to develop a data-driven, domain-aware, optimization-based attacker model. Using an expansion of this model, we compute several different attacks, including multiple simultaneous attacks, against a high-fidelity commercial building emulator and compare the impacts of those attacks to each other. One next step of interest is to construct a defender system, built on the same modelling approach, designed to detect and mitigate such attacks.

koopman operator, Cyber-Physical Security, machine↗

FEMP Cyber Security Arsenal

The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools.

Gourisetti, Sri Nikhil Gupta↗

FEMP Cyber Security Arsenal

The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. This is an upgrade of the tools available from the earlier version in DOE CODE ID: #41457

Gourisetti, Sri Nikhil Gupta↗

FEMP Cybersecurity Arsenal

The FEMP Cyber Security Arsenal is a family of cyber security tools for the federal facility owners and operators. Using these tools, facility owners can evaluate their overall cybersecurity posture. These tools are web-based front-end tools. The tools are meant to help federal owners and operators to evaluate their overall cybersecurity posture. These tools are developed based on the NIST Cybersecurity framework, risk management framework, and DOE C2M2 architectures. Version 3 provides significant updates and features in ten areas

Ashley, Travis [Pacific Northwest National Laborat↗

RAMSeS: Rapid Analysis of Mission Software Systems

Over the past few decades, software has become ubiquitous as it has been integrated into nearly every aspect of society, including household appliances, consumer electronics, industrial control systems, public utilities, government operations, and military systems. Consequently, many critical national security questions can no longer be answered convincingly without understanding software, including its purpose, its capabilities, its flaws, its communication, or how it processes and stores data. As software continues to become larger, more complex, and more widespread, our ability to answer important mission questions and reason about software in a timely way is falling behind. Today, to achieve such understanding of third-party software, we rely predominantly on the ability of reverse engineering experts to manually answer each particular mission question for every software system of interest. This approach often requires heroic human effort that nevertheless fails to meet current mission needs and will never scale to meet future needs. The result is an emerging crisis: a massive and expanding gap between the national security need to answer mission questions about software and our ability to do so. Sandia National Laboratories has established the Rapid Analysis of Mission Software Systems (RAMSeS) effort, a collaborative long-term effort aimed at dramatically improving our nation’s ability to answer mission questions about third-party software by growing an ecosystem of tools that augment the human reverse engineer through automation, interoperability, and reuse. Focusing on static analysis of binary programs, we are attempting to identify reusable software analysis components that advance our ability to reason about software, to automate useful aspects of the software analysis process, and to integrate new methodologies and capabilities into a working ecosystem of tools and experts. We aim to integrate existing tools where possible, adapt tools when modest modifications will enable them to interoperate, and implement missing capability when necessary. Although we do hope to automate a growing set of analysis tasks, we will approach this goal incrementally by assisting the human in an ever-widening range of tasks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Exceedance Response Action (ERA) Level 2 (Technical Report)

The Sandia National Laboratories, California (SNL/CA) site comprises approximately 410 acres and is located in the eastern portion of Livermore, Alameda County, California. The property is owned by the United States Department of Energy/National Nuclear Security Administration (DOE/NNSA) and is being managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS). Operations at the SNL/CA facility consist of DOE statutory responsibilities for nuclear weapon research and design, development of energy technologies, and basic scientific research. Specific industrial activities occur in discrete buildings and include electroplating or anodizing, machine shop, permitted hazardous waste treatment, storage and disposal facility (TSDF), and a scrap yard.

54 ENVIRONMENTAL SCIENCES↗

Towards a New Supply Chain Cybersecurity Risk Analysis Technique

Supply chain cyber-attacks, such as the SolarWinds Orion attack, are occurring with greater frequency. These attacks compromise a digital device before it is sent to customers, bypassing traditional security controls to remain persistent and undetected in operational environments. While supply chain attacks are prevalent, methods for analyzing the risk of these attacks are currently unavailable. This paper proposes new supply chain cyber-attack difficulty and risk metrics to evaluate the relative risk of an attack throughout the supply chain lifecycle. Difficulty metrics for each stakeholder in a digital device’s supply chain (e.g., hardware manufacturing, firmware development, software development, storage, and distribution entities) are calculated using scores from cybersecurity maturity questionnaires in a Bayesian Network leaky Noisy-MAX model. These difficulty metrics are then used to calculate an overall supply chain cyber-attack risk. Vulnerability and recoverability metrics are also proposed to evaluate the relative stakeholder influence in the attack risk. These proposed relative risk metrics enable continuous supply chain monitoring, provide decision-makers with information necessary for improved supplier selection, and help drive improvements in the cybersecurity posture of the stakeholders in their supply chain.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SOLAr Critical Infrastructure Energization (SOLACE): Leveraging Distributed Energy Resources to Provide Local Power

This document is a technical report based on a large-scale DOE-funded project conducted between 2019 and 2022. The project, called SOLAr Critical infrastructure Energization (SOLACE), is aimed at leveraging distributed energy resources (DERs) to provide local power to communities, feeders, or other regions. The project included a particular focus on high-value critical loads such as municipal water supply, telecommunication hubs, and disaster shelters. The key developments of the project were: (1) A comprehensive pre-event power system analysis methodology that identifies and characterizes the viable local power options. (2) A DMS-based example control system for activating and operating the local power solution during a time of crisis. (3) Grid-forming inverter technology to enable isolated local power operation and black-starting. (4) Cyber-security considerations for isolated systems when wider-area communication may be offline. This report describes the overall process that identifies and assesses the viable DER-based local power solutions for a given facility, region, or community. The report documents the process, including the key analysis steps, tools required, data requirements, and recommended pass/fail criteria for each step. It also provides a sample implementation of this process through a test case. Finally, it provides details of how a viable pre-event plan can be selected and activated at go-time when an event has occurred.

14 SOLAR ENERGY↗

Nuctech-SOP-Image_Reconstruction (includes signatures)

This Standard Operating Procedure (SOP) describes the steps to reconstruct x-ray projection images from Nuctech LS1516BS data captured at facilities operating in cooperation with the Department of Homeland Security (DHS) Explosives Threat Assessment Program (ETA). This document also provides the steps for evaluating and approving the quality of the reconstructed images.

42 ENGINEERING↗

Exceedance Response Action (ERA) Level 2 Technical Report Update

The Sandia National Laboratories, California (SNL/CA) site comprises approximately 410 acres and is located in the eastern portion of Livermore, Alameda County, California. The property is owned by the United States Department of Energy/National Nuclear Security Administration (DOE/NNSA) and is being managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS). Operations at the SNL/CA facility consist of DOE statutory responsibilities for nuclear weapon research and design, development of energy technologies, and basic scientific research. Specific industrial activities occur in discrete buildings and include electroplating or anodizing, machine shop, permitted hazardous waste treatment, storage and disposal facility (TSDF), and a scrap yard. This report provides an update to the ERA Level 2 Technical Report Update previously submitted in June 2022 (2022 ERA L2 Technical Report Update) for iron, aluminum, and pH. In accordance with the California’s General Permit for Discharges of Storm Water Associated with Industrial Activities (IGP) Section XII.D.3.c, an ERA Level 2 Technical Report update is to be submitted with the annual report when a facility utilizing an Industrial Activity Best Management Practice (BMP) Demonstration (IABMPD) experiences additional exceedances of the numeric action levels.

54 ENVIRONMENTAL SCIENCES↗