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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Computational and Systems Biology Advances to Enable Bioagent Agnostic Signatures

Enumerated threat agent lists have long driven biodefense priorities. The global SARS-CoV-2 pandemic demonstrated the limitations of searching for known threat agents as compared to a more agnostic approach. Recent technological advances are enabling agent-agnostic biodefense, especially through the integration of multi-modal observations of host-pathogen interactions directed by a human immunological model. Although well-developed technical assays exist for many aspects of human-pathogen interaction, the analytic methods and pipelines to combine and holistically interpret the results of such assays are immature and require further investments to exploit new technologies. In this manuscript, we discuss potential immunologically based bioagent-agnostic approaches and the computational tool gaps the community should prioritize filling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Controlled environment agriculture: An opportunity to strengthen interagency research collaboration in the US government

Challenges facing food production and agricultural systems are increasingly interconnected with economic, security, health, and equity issues, among others. Threats such as extreme weather, economic volatility, and shrinking water resources and arable land, influence our ability to maintain a safe and resilient food supply. One promising solution to these threats is controlled environment agriculture (CEA). In many cases, CEA can drastically reduce the amount of water and land used in crop production while increasing productivity. Operations may be established in nearly any environment and harvests can take place year-round, supporting food system resiliency and sustainability. CEA sits at the nexus of a number of disciplines and industries, making it well suited for transdisciplinary and multi-institutional research coordination. Herein, authors from multiple US government agencies present CEA as a case study in improving cross-agency research collaboration. The federal government houses a range of scientific expertise and research capabilities, positioning scientists to lead national and global efforts in transdisciplinary, interagency approaches to complex challenges. Navigating cross-agency collaboration can be a challenge, especially coordinating across different scientific disciplines, geographic locations, and funding mechanisms. To enhance multiagency efforts, collaborators could prioritize (i) organizing personnel and resources, (ii) enhancing existing multiagency collaborations, and (iii) focusing on further opportunities for coordination. Adopting these approaches could enable federal researchers to reinforce and advance academic and industry efforts to address current CEA challenges while solidifying the United States as a leader in this arena.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Elucidating Anthracnose Resistance Mechanisms in Sorghum—A Review

Sorghum (Sorghum bicolor) is the fifth most cultivated cereal crop in the world, traditionally providing food, feed, and fodder, but more recently also fermentable sugars for the production of renewable fuels and chemicals. The hemibiotrophic fungal pathogen Colletotrichum sublineola, the causal agent of anthracnose disease in sorghum, is prevalent in the warm and humid climates where much of the sorghum is cultivated and poses a serious threat to sorghum production. The use of anthracnose-resistant sorghum germplasm is the most environmentally and economically sustainable way to protect sorghum against this pathogen. Even though multiple anthracnose resistance loci have been mapped in diverse sorghum germplasm in recent years, the diversity in C. sublineola pathotypes at the local and regional levels means that these resistance genes are not equally effective in different areas of cultivation. This review summarizes the genetic and cytological data underlying sorghum’s defense response and describes recent developments that will enable a better understanding of the interactions between sorghum and C. sublineola at the molecular level. This includes releases of the sorghum genome and the draft genome of C. sublineola, the use of next-generation sequencing technologies to identify gene expression networks activated in response to infection, and improvements in methodologies to validate resistance genes, notably virus-induced and transgenic gene silencing approaches.

Plant Sciences↗
DOE OSTI2021

The “Brookhaven Brassie” and the Response to the Three Mile Island Accident

In the mid-1970s, American civil defense authorities became increasingly concerned with the potential threat of fission reactor accidents. Research from the Defense Civil Preparedness Agency began to be aimed not just at the ever-present threat of nuclear warfare, but also peacetime emergencies as part of a "dual use" philosophy. The Brookhaven National Laboratory received funding to create a prototype radioiodine air sampling system, with multiple publications detailing the creation of the air sampler itself and a special CD V-700 survey meter that accompanied it. In late March 1979, the system found its first operational employment at the reactor accident at Three Mile Island, Pennsylvania. Despite successful use and further study, the BNL Air Sampler was not widely fielded by the federal government. However, lessons learned from its employment and development may be applicable to contemporary radiological emergency response.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Cyber Protection of Grid-Connected Devices Through Embedded Online Security

Cybersecurity research regarding the electric power grid has primarily been focused on protecting the communication layer of grid-connected devices against cyber-attack threats. Although many developed methods have greatly reduced the effects of a cyber-attack on the vulnerabilities of grid-connected devices, discovering new vulnerabilities is inevitable and a constant threat. As a result, the overall reliability and security of network communications with regard to grid-connected devices is a concern. Here, this paper proposes a method that further secures a system by focusing on the control and hardware layer of grid-connected devices. The device’s controller firmware will be validated and authenticated using integrated device emulation resources prior to being activated to control the grid-connected device. This verification process is performed while the controller is online and actively controlling power flows related to the device. Therefore, an attack to the system through a malicious firmware patch would be detected by the online security and rejected while safely maintaining continuous and stable control of the device. This method integrates the concepts of firmware hot-patching, digital twins, and active monitoring into an overall cybersecurity protection system.

cybersecurity↗
DOE OSTI2020

Method for Assessment of Security-Relevant Settings in Anomaly-Based Intrusion Detection for Industrial Control Systems

Ensuring the integrity of Ethernet-based networks is a challenging and constantly evolving domain. This problem is exacerbated for those operational technology (OT) networks supporting industrial control systems (ICS) since much of that equipment was originally designed to be on a network that was isolated and generally considered free of malefactors. Increasing pressure to bridge these systems with traditional information technology (IT) networks has introduced a bevy of new threats. In response, both academia and industry have responded with security solutions tailored to ICS environments. Deploying these protection systems often involves several configuration choices. While some of these choices are clear (e.g., block/enable protocol X) others are far more subjective (e.g. alert threshold == 3.43). Further complicating the situation, while often similar to IT networks, OT networks have unique challenges and characteristics that make the task of protecting them simultaneously more difficult and straight forward.Extant solutions for quantifying the relative security of intrusion detection systems fail to effectively support the operators of said systems with understanding the impact of various configuration changes. Further, they assume that the attacks are static and not subject to manipulation or alteration in the face of defenses. In this paper, we present a threat-based method for quantifying the relative impact of various security settings for intrusion detection systems (IDSs) within ICS environments. This method provides operational staff with a clear understanding of the relative impact of their settings and assumes that the attacks levied against them are dynamic. The model is described in detail, we apply the model to a synthetic data set, and discuss the inferences that can be made and what types of decisions they could be used to support.

Gillen, Rob↗
DOE OSTI2024

Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing a enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlight potential aspects of the model for real-life applications.

Mathieu, Reynold↗
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 OSTI2021

Toward an Electromagnetic Event Resilient Grid

The motivation for writing this article is that the threat of a large-scale electromagnetic event having a negative impact on the electric grid is real. Whether human-caused, via the detonation of a nuclear device, or natural, via a high-intensity burst of solar radiation, our historic experience with these phenomena indicates that as a global community, we should be prepared for such events and know how to mitigate their impacts. Current studies and related discussions provide a wide range of damage assessments for these events. We recommend continuing current technical investigations and research as well as strengthening collaboration between stakeholders and experts. This would ensure future threats are addressed in a timely and effective manner.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Cybersecurity Challenges in Low-Inertia Power-Electronics-Dominated Grids

Here, the low inertia characteristics of the power electronics dominated grid (PEDG) introduces challenges while restoring voltage and frequency to their nominal values. These stability challenges create new cybersecurity vulnerabilities that are not thoroughly discussed in the literature. Cyber events such as false data injection (FDI), denial of service (DoS), man-in-the-middle attacks, stealthy attacks, and advanced persistent threats target PEDG to disrupt grid stability or gain financial benefits. The low inertia of PEDG (< 2s) compared to traditional grids (~10s) exacerbates these vulnerabilities. In response to stealthy attacks on state variables that supervisory layers cannot detect until significant harm occurs, the low inertia characteristics of PEDG offer substantial stealthy attack surfaces. To counteract such threats, PEDG must be equipped with ultra-fast real-time anomaly detection system and trajectory prediction mechanism to achieve effective cyberattack resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Cyber Attack Sequences Generation for Electric Power Grid

Security assessment of cyber-physical energy systems (CPESs) such as the electric power grid is a critical operation to maintain availability, reliability, and quality of service in the presence of persistent threats from malicious cyber actors. Existing security assessment approaches such as penetration testing and red teaming rely on subject matter expert experience and forensic cyber analysis of historical events to perform realistic, threat-informed assessments of CPES defense. CPESs have a large attack surface because of the heterogeneity and complexity of underlying topology, devices, measurements, and vulnerabilities. The aforementioned approaches lead to partial coverage of the attack surface with a large set of unknown but possible exploits. There is a need to automate the CPES attack surface discovery and contextualize it for relevant, highly probable, real-world attack scenarios. We propose a methodology and framework to facilitate the discovery of the CPES attack surface. We present a multilayer attack graph with ranked attack sequences to describe CPES failure scenarios. We present a work-in-progress framework that lists key components to automate the attack modeling and sequence generation. We demonstrate the published National Electric Sector Cybersecurity Organization Resource CPES failure scenario to highlight the trustworthiness of generated attack sequences.

Dutta, Ashutosh↗
DOE OSTI2023

Cybersecurity Value-at-Risk Framework

As more variable renewable energy sources are added to the grid, the role of hydropower as a reliable baseline and firming resource is growing more critical. However, the U.S hydropower fleet is not fully prepared to face modern issues such as cybersecurity threats. Hydropower accounts for 37% of U.S. utility-scale renewable electricity but is challenged by diverse infrastructure and legacy devices that predate modern security practices. While new cybersecurity solutions cannot simply be added to current hydropower generation and operation technologies, custom cybersecurity assessments can reveal system-specific threats and risk probabilities and identify mitigating enhancements.

cybersecurity valuation methodology↗
DOE OSTI2021

A Methodology for Assessing Risk to Inform Technology Integration

When new technology, such as artificial intelligence (AI), is introduced into an existing workflow it may impact risk by mitigating some vulnerabilities and threats in the workflow while introducing others. We present a versatile methodology for assessing the vulnerabilities and threats that impact overall risk in a workflow to inform technology integration. Our method involves both qualitative and quantitative assessment of risk and includes a formula for generating a risk score to guide technology integration. We describe our methodology and demonstrate its application to a specific workflow (the Derivative Classification review process). This work was funded by the Department of Energy (DOE) Automated Classification Tools for the Identification of Classified Information (ACTICI) program.

risk, technology integration↗
DOE OSTI2023

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↗
DOE OSTI2024

A Data-Driven Exploration of the Impact of Renewable Energy on Inter-Area Oscillations in the U.S. Eastern Interconnection

As increasing amounts of renewable energy (RE) resources are incorporated into the bulk-power grid, power system oscillations are expected to change. This work investigates how RE generation impacts the frequency and damping ratio (DR) of two dominant inter-area modes in the U.S. Eastern Interconnection (EI) using regularly updated estimates collected over a 12-month period. Quantile regression is used to derive the correlation between operating conditions and mode properties, and a bootstrap method is used to quantify the uncertainty associated with the correlation estimates. Results show that with an increase in system load, the frequency of a mode decreases and DR increases. Evidence that increasing RE generation results in an increase in frequency and decline in DR was found for one of the two modes studied. This work shows that increasing RE levels will impact the properties of inter-area oscillations in the EI, but it does not indicate the presence of immediate threats to grid stability. The outlined approach can be used to periodically assess changing mode properties as RE levels continue to grow and flag stability concerns before they become serious reliability threats.

Inter-area oscillation, mode meters, quantile regr↗
DOE OSTI2023

Alerga: Alert Aggregation and Reasoning in GOOSE Simulation Pipeline

IEC 61850 specifies the Generic Object Oriented Substation Event (GOOSE) protocol as one option for low latency communication of substation-related events. Due to its strict timing requirements, GOOSE lacks any form of encryption or authentication and has only minimal integrity guarantees. These absences render the protocol vulnerable to a variety of communication anomalies, including adversarial action. In particular, an adversary with access to the substation network can launch man in the middle (MITM) attacks. We propose Alerga, a set of tools to allow operators to mitigate some of the risks of the protocol while retaining its strengths. To that end, we have developed first a GOOSE simulation pipeline including data generation, anomaly detection, alert handling, causal reasoning and data visualization components. The simulator is designed to be modular, allowing operators to swap components to better fit their network capabilities. The volume of alert traffic on a substation network threatens operators with alert fatigue. In order to combat this, we secondly present a novel form of alert aggregation and processing, offering operators a condensed view of any threats to the system. Thirdly, to facilitate the handling of these threats, our causal reasoning system traces the alerts back to their most likely cause, generating an initial hypothesis for operators to investigate.

alert aggregation↗
DOE OSTI2023

A Computational Framework for Control Co-Design of Resilient Cyber–Physical Systems With Applications to Microgrids

Critical infrastructure networks, such as power and transportation networks, can be modelled as cyber-physical systems. As the complexity of such systems grow, there is need for developing metrics and design tools that will co-optimize the physical components of the system and the control policies to guarantee resilience against cyber and natural threats. To that end, we develop a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives. Here, the capabilities of the developed co-design engine is demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Data-Driven Cyber-Attack Detection for PV Farms via Time-Frequency Domain Features

The internetworking of grid-connected power electronics converters (PECs) in photovoltaic (PV) farms has inevitably expanded the cyber-attack surfaces. Here this paper presents a comprehensive study on cyber-attack detection and diagnosis for PEC-enabled PV farms via single waveform sensor to distinguish between normal conditions, open-circuit faults, short-circuit faults, and cyber-attacks. To our knowledge, this has not been attempted before. Firstly, we propose frequency-domain magnitude-based residuals to identify short-circuit faults and a time-domain mean current vector-based feature to distinguish open-circuit faults from other threats. These features can fully reflect the specific physical characteristics of PV farms during threat duration. Secondly, unlike micro phasor measurement units (µPMU) and raw electric waveform-based methods, the proposed innovative features can address novel cyber-attacks that are excluded from the training process. Thirdly, an online hardware-in-the-loop (HIL) testbed using the OPAL-RT real-time digital simulator has verified the effectiveness. The monitoring system runs in real-time while using HIL as an operational solar farm and a National Instruments (NI) data acquisition card as the electric waveform sensor at the point of coupling.

42 ENGINEERING↗