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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cybersecurity Resiliency of Marine Renewable Energy Systems-Part 1: Identifying Cybersecurity Vulnerabilities and Determining Risk

Technology innovation, market demand, and the potential impacts of a changing climate are driving the marine renewable energy (MRE) industry to develop market-ready systems to provide low-carbon electricity for emerging, off-grid markets. The advanced operational and information technology devices used in MRE systems create a pathway for a cyber threat actor to gain unauthorized access to data or disrupt operation. To improve the resiliency of MRE systems as a predictable, affordable, and reliable source of energy from oceans and rivers, guidance was developed for an end users' organization that describes a framework for identifying and managing cybersecurity risk. The development of the cybersecurity guidance is based on standards described in the Risk Management Framework and Cybersecurity Framework developed by the National Institute of Standards and Technology (NIST). This paper is the first of a two-part series that describes an approach to determine the cybersecurity risk for MRE systems based on assessing potential cyber threats, identifying vulnerabilities (people, processes, and technology, including physical and operational environment), and evaluating the consequences a cyberattack would have on operation of the MRE system and impact on end users' mission and business objectives. MRE developers and stakeholders can use this approach to assess their current cybersecurity risk posture to incorporate appropriate cybersecurity controls to reduce the consequences and impacts from a cyberattack on MRE systems. This approach can be refined further as MRE systems are deployed and operational configurations are available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

IMPLEMENTING CYBERSECURITY INTO AN EXISTING NATIONAL NUCLEAR NON-PROLIFERATION PROGRAMME – A CASE STUDY

Cyber threat profiling and risk mitigation is critical to any nuclear state organization and should be considered as part of any comprehensive nuclear security programme. Defining and evaluating the impact of the cyber threat to mission can be challenging. An existing national nuclear non-proliferation organization undertook an effort to incorporate computer security activities into its programme to address cyber risk. One of the primary goals of this endeavour was to develop a set of prioritised recommendations for organizational follow-through. The organization dedicated subject matter expert resources in the form of a cyber task force to support this goal. Opportunities were identified where computer security could be built into each programme including office-level strategies and tools. Of course, no new identified threat vector is easily considered and incorporated into existing programmes without impact. There are many obstacles to be overcome. Technically literate subject matter experts are difficult to find, management has comparatively less experience applying computer security into its programmes, and trying to change the culture to consider computer security risk at policy and programmatic levels takes time and management attention. As an outcome of this process, a roadmap for program integration was developed, including the establishment of a cyber support team. This paper will discuss the challenges and successes associated with establishing such a team.

Cyber Security, Nuclear, Non-proliferation↗
DOE OSTI2025

Enhancing the Survivability of Power Systems With Grid-Edge DERs Against DoS Attacks

Power system survivability, defined as the ability of a system to maintain steady-state functionality under varying operational conditions, reflects its resilience against disturbances. While existing research primarily focuses on physical-layer disturbances, the increasing prevalence of grid-edge DERs, which are primarily used for integrating renewable energy, has significantly expanded the cyber attack surface. As a result, operational disruptions caused by cyber threats are posing significant challenges to system survivability and cannot be overlooked. To fill this gap, we redefine system survivability to incorporate the cyber layer’s status and propose a Distributionally Robust Optimization (DRO) approach to enhance power system survivability against potential cyber-physical threats. In this paper, we first analyze the operational guidelines of systems with a high penetration of DERs under various cyber network conditions and redefine survivability in this context. Next, we focus on the most common cyber threat, Denial-of-Service (DoS) attacks, and develop a corresponding attack model. This model allows for the creation of a kernel-based ambiguity set that captures attack uncertainties using historical data. Finally, we transform the proposed DRO model as a tractable optimization problem, with its solution providing an optimal cyber redundancy plan to enhance system survivability in DoS attack scenarios. Simulation results on the IEEE 13-node and 123-node test feeders demonstrate the effectiveness of our proposed model in improving system survivability. This model can also be expanded to include other types of common attacks and serve as a comprehensive planning tool to improve overall cyber physical survival of the system.

cybersecurity↗
DOE OSTI2024

RESCue Model (RESCue Experiment and Model) [SWR-24-84]

The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. The research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf

Hasandka, Adarsh↗
DOE OSTI2022

Implementation Aspects of Smart Grids Cyber-Security Cross-Layered Framework for Critical Infrastructure Operation

Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.

cross-layered↗
DOE OSTI2024

Renewable Energy and Storage Cybersecurity Research (RESCue) Pilot Final Report

The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of distributed energy resources (DERs) and transmission-connected hybrid renewable energy systems against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. This publication the final report for the first year of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cybersecurity Assessment in DER-rich Distribution Operations: Criticality Levels and Impact Analysis

The integration of distributed energy resources (DERs) in distribution networks has become a pivotal strategy for achieving decarbonization, enhancing grid resilience, and optimizing grid efficiency. Remote monitoring and control op- erations of such resources rely on a network of sensors and communication infrastructure, exposing the system to potential cyber threats. Therefore, as the deployment of DERs increases, ensuring secure monitoring and control becomes an imperative challenge. This paper utilizes real-time feeder models, which are instrumental in developing cybersecurity testbeds tailored for hardware-in-loop (HIL) systems. These models enable users to simulate cyber attacks in a real-world environment and analyze the power distribution operations during vulnerabilities. Furthermore, we discuss several practical sets of grid parameters to identify critical levels of DERs and evaluate various scenarios that simulate cyber threats on sensitive DERs. The modified IEEE 123-bus model is used as the test case for demonstrating the proposed scenarios. The findings from this study provide valuable insights into the vulnerabilities and potential consequences of cyber attacks on DERs, allowing for better mitigation strategies and improved cyber resilience in future distribution networks.

Maharjan, Manisha↗
DOE OSTI2025

PSA 2025 DPRA for Cyber Optimization

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Evaluating defense options should include quantitative evaluation of overall effectiveness to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation and have difficulty with time dependent scenarios. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related integrity is a requirement set by the U.S. Nuclear Regulatory Commission. But companies are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want reliability analysis while optimizing cost, which requires more than safety modeling methods. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with timing and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues such as state-base explosion found in Markov-based tools. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Equipment Assessment Guide: A Technical Inspection and Hardening Guide for Devices in Power Grid Operations

This Equipment Assessment Guide, developed by Idaho National Laboratory (INL), provides a comprehensive framework designed to enhance the security of operational technology (OT) devices within power grid operations. The guide outlines essential steps for asset owners to conduct technical inspections and harden vulnerable hardware and firmware components commonly found in embedded systems. It focuses on components frequently targeted by cyber threats, offering valuable identification techniques for locating and recognizing critical components on devices. Additionally, the guide presents recommended secure configurations aimed at minimizing exposure and reinforcing defenses, along with impact analysis that highlights the potential consequences for grid operations if components are compromised. By implementing the recommendations outlined in this guide, asset owners can significantly enhance their cybersecurity posture, reduce the attack surface of field-deployed devices, and improve the resilience of grid services against emerging cyber threats.

42 - ENGINEERING↗
DOE OSTI2025

Countering Weapons of Mass Destruction (CWMD) Zero Trust Framework: CWMD Zero Trust Principles Model

The research focuses on the critical need for enhanced cybersecurity within the Countering Weapons of Mass Destruction (CWMD) Office, specifically targeting Chemical, Biological, Radiological, and Nuclear devices. Traditional perimeter-based security models are insufficient against modern cyber threats, prompting a shift toward Zero Trust principles (ZTP) that emphasize continuous verification and stringent security for all devices. Federal directives mandate the adoption of Zero Trust (ZT) across agencies, supported by guidelines from National Institute of Standards and Technology (NIST), U.S. Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA), U.S. Department of Defense (DoD) and National Security Agency (NSA). The research involved mapping ZT guidance from these agencies to develop tailored CWMD ZTP. The study identified gaps and areas for improvement, including clear transitional guidance from traditional to ZT architectures and the focus on explicit cross cutting capabilities. Design improvements are recommended to ensure increased comprehensive protection and resilience against sophisticated cyber threats for Chemical, Biological, Radiological, and Nuclear (CBRN) devices. Collaborative efforts among federal agencies are essential for the successful deployment of an optimized ZT guidance.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Achieving American Leadership in Cybersecurity and Digital Components Factsheet

The Biden Administration’s efforts to meet 100% clean electricity by 2035 and net-zero greenhouse gas emissions by 2050 has created opportunities to rebuild American supply chains create new jobs, strengthen community engagement, and spur U.S. economic growth. DOE’s strategy for success in the transition to a clean energy economy hinges on building and maintaining technology supply chains that are advanced, secure, and resilient to cyber threats. As the energy sector grows increasingly globalized, complex, and digitized, the supply chain for digital components of energy systems – including software, virtual platforms and services, and data – is facing greater threats. Nearly all digital components of U.S. energy sector systems are vulnerable to cyber supply chain instability, stemming from a variety of causes and shared among a broad set of interdependent stakeholders. Overall, supply chain risks for digital components in energy sector systems will continue to evolve and likely increase as these systems are increasingly interconnected, digitized, and remotely operated.

CCE↗
DOE OSTI2021

Critical Roles of Information, Analysis, Research, and Operations in the Cyber Realm

PNNL has developed an adaptive cyber integration framework (ACIF) to facilitate the timely sharing of cyber threat information along with the advancement of situational awareness tools to enhance protection against and respond to critical infrastructure cybersecurity threats. The ACIF comprises components implemented iteratively to achieve research and mission goals. The ACIF components include data generation technologies, analytic tools development and maturation, data enrichment and fusion, trust building with stakeholders, investigative research, analytic rigor, production, and dissemination. Each component, its importance to the ACIF, and how they can be adopted and applied across other information-sharing sectors and domains are discussed in this paper.

Cyber Threat Intelligence, Cyber Security, Data En↗
DOE OSTI2025

Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems

As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.

Williams, Bethanie [Tennessee Technological Univer↗
DOE OSTI2022

Smart Microgrids

The Nation’s electrical power depends on one bulk power grid to support security and economic prosperity. According to the Department of Homeland Security’s Homeland Threat Assessment of 2020, the largest cyber threat to homeland security is potential disruption to critical infrastructure, including power grids. Critical infrastructure includes the physical and cyber systems which generate, transmit, and distribute electricity with an impact on economic security, public health, or safety. The surety of the Nation’s power grid is vital for providing essential services and would put the population at risk if disrupted. Power outages can have catastrophic consequences for critical organizations such as hospitals and military installations. Additionally, the current fossil-fuel dependent power grid is extremely fragile and vulnerable to overloads, storms that destroy power lines, and cyber-attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗