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At least 307 records · Page 17

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DOE OSTI2024

Field Programmable Gate Array Data Capture for Control Systems

Some Industrial Control Systems (ICS) networks are based on protocols such as Serial and Industrial Ethernet. These protocols currently have no existing cybersecurity monitoring tools, leaving a large gap in the cyber defense of critical infrastructure. In order to analyze such ICS traffic, it is first necessary to implement methods of capturing the ICS data. Whereas traditional methods of analyzing data would use microprocessors, the nature of high-speed analog data can be difficult to implement on such a versatile processor, as they are rather inefficient for doing a single task. Whereas Field Programmable Gate Arrays (FPGAs) provide an adequate tool in analyzing high speed data, as despite the lack of program versatility, Programmable Logic can implement a solution with minimal clock cycles, allowing time for each new packet of data to be captured before a new data sample is taken.

42 ENGINEERING↗

DOE OSTI2025

Digital Assurance Checklist for Homeowners and Installers

This document provides a comprehensive Digital Assurance Checklist for securing behind-the-meter energy assets, focusing on both installers and homeowners. As distributed energy resources (DERs) such as solar PV and battery storage become integral to residential energy systems, cybersecurity emerges as a critical component of reliability and safety. The guide outlines actionable steps for installers during pre-installation, commissioning, and post-installation phases, emphasizing practices like network segmentation, credential management, firmware validation, and homeowner education. For homeowners, the document introduces a tiered approach to cyber hygiene—from essential measures like strong Wi-Fi credentials and automatic updates to advanced strategies such as network segmentation, DNS filtering, and intrusion detection. By adopting these practices, stakeholders can mitigate cyber risks, safeguard energy infrastructure, and ensure resilient, secure operation of DER systems. Additional resources and references to industry standards are included to support implementation.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Sequence-Based Anomaly Detection in Critical Infrastructure Networks

United States critical infrastructure faces new cyber threats from adversarial nation-state actors in the form of malware-free attacks. Traditional cybersecurity techniques use rules-based methods to identify indicators of compromise on networks, often missing these sophisticated attacks. Our approach leverages multiple state of the art machine learning models in a pipeline to identify abnormal network events through sequential analysis. We combine both device and packet-level information into individual events to characterize anomalous network actions. The model is trained and tested on real network traffic from the Idaho National Lab High Performance Computing (HPC) with greater than 98% precision. It is capable of flagging malicious tactics used by adversaries in malware-free attacks, severe changes to the network, and abnormal user activity by network devices.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Energy Sector Threat Brief: 2024 Round Up

What major and minor cybersecurity events affected the energy sector in the last year? What trends were observed in the events, disclosure of vulnerabilities, and other headline news? This talk will focus on real-world events put in the context of an evolving geo-political landscape. We will discuss events that had operational impact as well as events affecting third-parties with exploration of how the impact of incidents is changing as more stakeholders are involved in new projects and the complexity of the modern grid. We will focus on lessons learned from the 2024 trends that operators and their partners can apply to stay ahead of the threats in 2025.

14 - SOLAR ENERGY↗

DOE OSTI2025

IT vs. OT: Trends and Incidents

This presentation discusses the differences between information systems (IT) and operational systems (OT) and why that difference is important in the context of cybersecurity for the energy sector.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2025

Braxton Marlatt Intern Poster

The Internet of Things (IoT) encompasses a vast network of interconnected devices embedded with software, sensors, and network connectivity, enabling data collection and exchange. While IoT technology revolutionizes various industries, it also introduces significant security challenges. This research focuses on enhancing IoT security through the implementation of Zero Trust Architecture concepts, specifically targeting the Network and Device pillars of the Cybersecurity and Infrastructure Security Agency’s Zero Trust Maturity Model. By generating Codified Attack Surfaces (CAS) using custom Structured Threat Information eXpression bundles, this project aims to provide enhanced visibility into network communications, detect vulnerabilities in device firmware, and improve the overall security posture for IoT devices and networks. The methodology involves defining custom STIX schema and objects, collecting data from intra-IoT traffic, external network traffic, and firmware analysis, and automating the conversion and correlation of this data into STIX bundles. The automated generation of attack surfaces offers comprehensive insights into activity, vulnerabilities, and anomalies within an IoT environment, enabling proactive threat identification and mitigation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Advanced Transmission Technologies – GETs and HPCs Session 1: ATT Foundations and Dynamic Line Ratings (DLRs)

The INL TADA GETs Cohort Session 1, held on November 4, 2025, convened experts to address the integration of advanced transmission technologies, including Grid-Enhancing Technologies (GETs) and High Performance Conductors (HPCs), with a focus on digital assurance challenges. The session highlighted the growing importance of cybersecurity, supply chain transparency, reliability, and business risk management in deploying GETs, especially Dynamic Line Ratings (DLRs). Participants examined how expanded attack surfaces, limited vendor pools, and new regulatory requirements—such as FERC Orders 881, 2023, and 1920—are influencing utilities and technology providers. The workshop underscored the need for cyber-informed engineering, secure-by-design principles, and practical risk management strategies, while fostering collaboration and knowledge sharing among industry peers. Technical discussions covered the evolution from static to dynamic line ratings, complexities of cloud-based architectures, and NERC CIP compliance challenges. The session concluded with a collaborative risk exercise and a preview of future workshops on advanced power flow control and transmission topology optimization, reinforcing the cohort’s commitment to advancing digital assurance in the energy sector.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session One - Abridged

The TADA BESS Supply Chain Workshops are designed to equip participants with the knowledge and tools necessary to address the evolving challenges at the intersection of battery energy storage systems (BESS), cybersecurity, and supply chain vulnerabilities. The workshops emphasize the application of Cyber-Informed Engineering (CIE) principles using INL’s procurement guide and the CIE-BAT tool. Attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their BESS projects. Additionally, the program fosters a collaborative network of practitioners and provides guidance on navigating emerging regulatory requirements, including FEOC rules under the OBBB framework, to assess and enhance organizational readiness. This is Session 1 of 3.

25 - ENERGY STORAGE↗

DOE OSTI2026

Large Load Integration - Task List and Overview

Large Load Integration Tasks: Task 1 – Workshops Support stakeholder engagement across industry to promote collaboration and identify solutions to challenges that will guide other work Task 2 – Ancillary Services Characterize different types of large loads to assess under what conditions they may be utilized to provide grid stability services Task 3 – Communications Explore the cybersecurity and communications infrastructure required to enable large loads to interface with grid operations to provide ancillary services Task 4 – Nuclear Integration Explore risks and methods for supporting large load energy needs with SMRs and incorporating them into the wider power system Task 5 – Decision Support and TA Provide support to stakeholders through the creation of planning tools and direct technical assistance.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Digital Assurance Checklist for Homeowners and Installers

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Towards Secure Autonomous Vehicles: An Integrated Edge and Multi-Modal Machine Learning Framework for Intrusion Detection

Autonomous vehicles (AVs) are vulnerable to cyberattacks targeting both internal communication networks and external perception sensors. While edge-based intrusion de- tection for Controller Area Network (CAN) buses offers real-time protection, it cannot detect cross-modal threats. Conversely, multi-modal fusion approaches improve coverage but often lack efficiency for in-vehicle deployment. This thesis integrates two complemen- tary solutions: (1) a lightweight, edge-deployable machine learning framework for CAN bus intrusion detection, and (2) a late-fusion system combining CAN FD and LiDAR data. Together, they form a hierarchical defense capable of handling single-modality and coordi- nated attacks. Simulations show that CAN-only models reach 93% accuracy on simulated DoS, spoofing, replay, and fuzzy attacks, while the fusion system achieves 0.87 AUC and 0.82 F1-score at 2 ms latency. This unified framework establishes a scalable, explainable, and field-ready strategy for AV cybersecurity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

BESS Digital Assurance, Supply Chain Risk Management, and Emerging Regulation Session One

25 - ENERGY STORAGE↗

DOE OSTI2026

CONTROL AND DATA ACQUISITION IN A CYBER-PHYSICAL MIDSTREAM TESTBED

This thesis presents the development of a laboratory-scale cyber–physical midstream pipeline testbed designed to address this gap and support research in industrial control systems security. The platform integrates pumps, valves, sensors, programmable logic controllers (PLCs), and a human–machine interface (HMI) to emulate the monitoring and control architecture of real pipeline operations. The physical process is implemented as a closed-loop liquid circulation system designed to replicate flow behavior characteristic of midstream pipeline infrastructure. The testbed enables real-time data acquisition of key process variables, including flow rate and pressure facilitating the generation of datasets representative of normal pipeline operation. A threat model encompassing common ICS attack vectors was developed, including sensor spoofing, command injection, false data injection, denial-of-service attacks, and relay manipulation. Multiple attack scenarios were implemented and evaluated to demonstrate how cyber intrusions targeting sensors, actuators, networks, and software propagate into measurable physical consequences in pipeline flow and pressure. The developed platform serves as a practical, cost-effective environment for experimentation, education, and future cybersecurity research in midstream pipeline systems.

42 ENGINEERING↗

DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

DOE OSTI2024

Pathways to commercial building plug and process load efficiency and control

Abstract To accomplish net-zero carbon emissions in the built environment by 2050, we must equitably decarbonize commercial buildings, including reducing plug and process loads (PPLs). PPLs are plug-in or hardwired electric and gas loads that are not associated with major building end uses like lighting and HVAC. Research shows PPL energy reduction strategies and control technologies have the potential to save energy. But even when implemented, these savings have rarely been achieved and there has not been widespread uptake in U.S. commercial buildings. We investigate why these technologies and strategies have not seen widespread adoption and identify behavior and technology pathways to increase PPL reduction in U.S. commercial buildings. We examined behaviors of commercial building stakeholders through 44 interviews and cross-referenced qualitative analysis findings with in-depth technical knowledge of existing PPL control technologies and reduction strategies. PPL control implementation must be paired with management strategies, such as occupant engagement and training, to achieve optimal savings, and best practices should be disseminated across the industry. We found that increasing access to cost and energy savings data will promote uptake of PPL control technologies and allow designers to better incorporate PPLs into building design. Improving access to funding for PPL energy efficiency projects and addressing the split-incentive problem will increase adoption of PPL efficiency and control. Code bodies should continue to include PPL monitoring and reduction measures in energy codes. Key building stakeholders, including cybersecurity and information technology teams, should be involved in PPL monitoring and reduction strategy processes for successful implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Designing resilient IoT and Edge Computing with federated tinyML

The rapid growth of the Internet of Things (IoT) and Edge Computing (EC) has brought significant conveniences to modern society but has also greatly expanded the cyber attack surfaces, particularly as these technologies are being increasingly integrated into critical systems such as power grids, healthcare, and smart homes. Here, to improve IoT/EC’s cybersecurity posture, we leveraged Artificial Intelligence (AI) and Machine Learning (ML) by employing tinyML to monitor voluminous IoT data for cyber threats while addressing devices’ resource constraints, and utilizing Federated Learning (FL) to share local detection knowledge across the system while preserving privacy. Building on our three-layer architecture combining tinyML and FL to enhance autonomous cyber attack detection, this paper demonstrated that the architecture improves detection accuracy, reduces resource consumption, and enables lightweight, secure IoT device monitoring. These results were validated using the public N-BaIoT dataset as well as real IoT network traffic data collected under multiple attack scenarios from our testbeds. Additionally, we introduced an enhanced FL methodology with a novel preprocessing stage, including federated feature selection and global preprocessor construction, to address IoT/EC data heterogeneity. We developed a physical IoT testbed for attack simulations and data collection, implemented a tinyML-powered detector for realistic model validation, and also built a virtual testbed for scalable evaluations of FL models across diverse network environments.

Cognitive cyber↗

DOE OSTI2025

FL‐ADS: Federated learning anomaly detection system for distributed energy resource networks

Abstract With the ongoing development of Distributed Energy Resources (DER) communication networks, the imperative for strong cybersecurity and data privacy safeguards is increasingly evident. DER networks, which rely on protocols such as Distributed Network Protocol 3 and Modbus, are susceptible to cyberattacks such as data integrity breaches and denial of service due to their inherent security vulnerabilities. This paper introduces an innovative Federated Learning (FL)‐based anomaly detection system designed to enhance the security of DER networks while preserving data privacy. Our models leverage Vertical and Horizontal Federated Learning to enable collaborative learning while preserving data privacy, exchanging only non‐sensitive information, such as model parameters, and maintaining the privacy of DER clients' raw data. The effectiveness of the models is demonstrated through its evaluation on datasets representative of real‐world DER scenarios, showcasing significant improvements in accuracy and F1‐score across all clients compared to the traditional baseline model. Additionally, this work demonstrates a consistent reduction in loss function over multiple FL rounds, further validating its efficacy and offering a robust solution that balances effective anomaly detection with stringent data privacy needs.

Purohit, Shaurya [Iowa State University Ames Iowa ↗

DOE OSTI2024

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗