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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Resilience Through Data-Driven, Intelligent Designed Control: A Formal Methods Approach

The PNNL and GTRI team developed a strategy to integrate temporal logic rule specification for detection of cyber-intrusion in the source code and control algorithms of CPS using advanced cyber-data. The GTRI team utilized its capabilities in rule synthesis and temporal logic specifications for software assurance and verification to detect and predict impact of cyber-intrusions and malware in the computational and control algorithms of cyber-physical systems. The team also developed a testing and verification approach that could be used to validate the suggested approach against a realistic use-case CPS showcasing improvements in system impact prediction performance. Temporal logic offers a compact expression of events in absolute and relative time and has a formalized translation to state machines. As such, temporal logic rules can feasibly be synthesized to any system as a rule engine, with the process being formally verified to be correct. The goal here is to utilize temporal logic rules to detect cyber-attacks and manipulations in the computational algorithms and provide real-time software assurance and verification guarantees.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Nominal and adversarial synthetic PMU data for standard IEEE test systems

GridSTAGE (Spatio-Temporal Adversarial scenario GEneration) is a framework for the simulation of adversarial scenarios and the generation of multivariate spatio-temporal data in cyber-physical systems. GridSTAGE is developed based on Matlab and leverages Power System Toolbox (PST) where the evolution of the power network is governed by nonlinear differential equations. Using GridSTAGE, one can create several event scenarios that correspond to several operating states of the power network by enabling or disabling any of the following: faults, AGC control, PSS control, exciter control, load changes, generation changes, and different types of cyber-attacks. Standard IEEE bus system data is used to define the power system environment. GridSTAGE emulates the data from PMU and SCADA sensors. The rate of frequency and location of the sensors can be adjusted as well. Detailed instructions on generating data scenarios with different system topologies, attack characteristics, load characteristics, sensor configuration, control parameters are available in the Github repository - https://github.com/pnnl/GridSTAGE. There is no existing adversarial data-generation framework that can incorporate several attack characteristics and yield adversarial PMU data. The GridSTAGE framework currently supports simulation of False Data Injection attacks (such as a ramp, step, random, trapezoidal, multiplicative, replay, freezing) and Denial of Service attacks (such as time-delay, packet-loss) on PMU data. Furthermore, it supports generating spatio-temporal time-series data corresponding to several random load changes across the network or corresponding to several generation changes. A Koopman mode decomposition (KMD) based algorithm to detect and identify the false data attacks in real-time is proposed in https://ieeexplore.ieee.org/document/9303022. Machine learning-based predictive models are developed to capture the dynamics of the underlying power system with a high level of accuracy under various operating conditions for IEEE 68 bus system. The corresponding machine learning models are available at https://github.com/pnnl/grid_prediction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Feature Classification for Control System Devices

Control systems are used to automate industrial processes, smart grids, and smart cities. Unfortunately, cyber attacks on control systems are on the rise. Additionally, control systems lack the plethora of tools available for commodity systems for forensic investigation. An important step towards the proper forensic investigation is to analyze device memory. To assist in identifying features of device memory, we present a machine learning-based technique that integrates ontology information for feature classification in a control system device’s memory.

ahmed mithu, M Rayhan↗
DOE OSTI2025

Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

comparison↗
DOE OSTI2022

Cyber-Resilient Frequency Control of Power Grids with Energy Storage Systems

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation. This paper proposes a defense methodology for the design of resilient operating constraints imposed on each generation and storage unit in order to prevent any attack sequence from driving the system's frequency to unsafe conditions. The resilient operating constraints are found by using ellipsoidal approximations of the reachable set of the power system, leading to a convex optimization problem with linear matrix inequalities. Numerical results in a single-area power system with synchronous generation and energy storage demonstrate how the resilient constraints provide security guarantees against any type of attack affecting frequency measurements or controller setpoints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

An Advanced Cyber-Physical System Security Testbed for Substation Automation

A Cyber-Physical System (CPS) testbed serves as a powerful platform for testing and validating cyber intrusion detection and mitigation strategies in substations. This study presents the design and development of a CPS testbed that can effectively assess the real-time dynamics of a substation. Cyber attacks exploiting IEC 61850-based SV and GOOSE protocols are demonstrated using the testbed, along with an analysis on attack detection. Realistic timing measurements are obtained, and the time frames for deploying detection and mitigation strategies are evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Privacy-preserving Information Security for the Energy Grid of Things

Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. Further, as information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacy-preserving, trust-augmented secure scheme for a smart grid implementation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Recommended Functionalities for Improving Cybersecurity of Distributed Energy Resources: Preprint

The legacy electric grid is transitioning into a 'present' modern grid due to increasing penetration of intermittent renewable generation at the distribution side, also known as distributed energy resources (DERs). Monitoring and control of such DERs requires extensive data-exchange and bidirectional communication networks. This bidirectional communication paves the way to cyber vulnerabilities and risks for new kinds of cyber-attacks that may have destructive impacts on power system operations. Since IEEE Std. 1547-2018 does not discuss cybersecurity measures for DERs, cybersecurity controls should be developed for securing DER systems at all three levels: device level, communications level, and applications level. This paper discusses the current industry's best practices related to DER cybersecurity and proposes recommended functionalities for improving the cybersecurity posture of DERs. These practical recommended functionalities have been discussed and verified with the industry through a DER cybersecurity working group and are meant to improve the device level security of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

IS BLOCKCHAIN A SUITABLE TECHNOLOGY FOR ENSURING THE INTEGRITY OF DATA SHARED BY LIGHTING AND OTHER BUILDING SYSTEMS?

Increasing amounts of data are available from lighting and other building systems. In commercial buildings, these data can be used to improve system and energy performance, detect and diagnose faults, and facilitate maintenance. Building data are not only of interest to owners and operators of the building systems, however. Owners and operators of similar buildings, manufacturers of building systems, utilities, and city agencies also have interesting use cases. Energy data can, for example, be used to verify the performance of energy-conservation measures, issue renewableenergy certificates, and financially settle grid services. Increased data sharing, however, significantly expands the cyber-attack surface, creating new challenges. In this work, blockchain is explored as an option for ensuring the integrity of data that are shared by lighting and other building systems. Blockchain fundamentals and variants are briefly reviewed, and value propositions relevant to building systems are discussed. A recently developed blockchain applicability framework (BAF) that builds upon and addresses the limitations of previous applicability models is also briefly reviewed. The BAF is used to assess the suitability of blockchain over other technologies or approaches for building-data applications, using emerging connected lighting systems as an example use case.

blockchain, connected lighting system, data integr↗
DOE OSTI2021

Control-Theory-Informed Feature Selection for Detecting Malicious Tampering in Additive Layer Manufacturing Processes

Additive layer manufacturing (ALM) is rapidly becoming an appealing solution to the low-volume manufacturing of metal, polymer, or composite parts. However, ALM’s reliance on digital part specifications, microcontrollers, and modern networking makes these devices vulnerable to malicious tampering by cyber attackers, which can negatively affect part performance and even result in catastrophic failure. We present a hybrid analytic approach to feature discovery using control theoretic techniques and linear modelling on input-output data collected from a representative controller system. Employing this approach, we design, train, and test an anomaly detection system. The preliminary results show that the proposed approach effectively discovers useful input-output relationships for anomaly detection in a simulated ALM process. Application to larger and more complex systems are discussed.

Dawson, Joel↗
DOE OSTI2021

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Protecting Smart Buildings with STIG

This is a submission for the 2022 Intern Poster Session. The abstract of the poster is: Smart buildings are getting more common, and so are hackers that target them. The physical systems in our businesses and homes are now vulnerable to cyber attacks. Using STIG, an INL program that turns cybersecurity data into graphs, buildings can be better protected.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

OPERATIONAL TECHNOLOGY BEHAVIORAL ANALYTICS (OTBA) – A DATA-CENTRIC APPROACH FOR REDUCING CYBERSECURITY RISK

This paper provides a summary of the methodology, findings, lessons learned, and insights from an investigation into the feasibility of the Operational Technology Behavioral Analytics (OTBA) cybersecurity approach. The concept was evaluated with data from the National Carbon Capture Center (NCCC) – a U.S. Department of Energy (DOE) funded facility that is managed and operated by Southern Company at Alabama Power’s E. C. Gaston generating power plant in Wilsonville, Alabama. Appropriate data sources for the post-combustion carbon capture system were identified. Infrastructure was deployed to monitor, capture and archive data for the system. Critical parameters for each subsystem were identified and analyzed. Machine-learning algorithms were used to establish and characterize normal operations and subsequently identify anomalies. This effort yielded valuable insights and formed the basis of a data-centric strategy for detecting cyber-attacks along with a coordinated response philosophy. A significant takeaway is that the OTBA cybersecurity approach is quite portable; it can be applied to other critical infrastructure beyond fossil power generation.

Black, Clifton↗
DOE OSTI2022

Variable Resource Resilience: How Systems Experience Increased Resilience from Variable and Hybrid Resources

Variable resources like wind and solar are often seen as detriments to system resilience rather than benefits because they may not be available with the capacities or services required during a high-impact low-frequency (HILF) event, whether that is a physical threat, natural disaster, or cyber attack. However, resilience goals and metrics are inadequate for electric energy delivery systems with inverter-based resources. Examination of this topic reveals that renewable resources are well suited to combat many resilience hazards due to local resource availability. Metrics that demonstrate the resilience value of variable resources are presented and categorized for resource (wind, solar, storage, hybrid) and installation type (bulk utility scale, behind-the-meter, front-of-the-meter, isolated). Distributed and hybrid systems can further enhance resilience benefits my maximizing resource potential for a locality. A case study demonstrating quantitative resilience benefits from wind alone is provided for St. Mary's, AK, which concludes that hundreds of thousands of dollars are saved by the addition of a wind turbine in the face of realistic fuel shortage and extreme winter weather scenarios.

17 WIND ENERGY↗
DOE OSTI2023

All Hazards Approach to Grid Modernization

Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward

17 WIND ENERGY↗
DOE OSTI2024

OT Operational Anomaly Detection (OAD) T&D + DER

The growth of utility-scale renewable energy resources, distributed energy resources (DER), and transportation electrification has increased uncertainty and cybersecurity risks in power grids. The Purdue Enterprise Reference Architecture model which is widely adopted by the utility industry is now insufficient to protect the power grid against cyber-attacks. There is a need to identify what cybersecurity model is effective on Energy Management System (EMS), Advanced Distribution Management System (ADMS), and DER Management System (DERMS) to address the fundamental cybersecurity challenges in the age of increasing renewable energy and DER share as well as consumer participation in the electric energy industry. The next generation of cybersecurity model for OT network should be able to detect inside attackers, mitigate the cybersecurity risks arising from the new grid participants including DER aggregators, electric vehicle owners, and behind-the-meter consumers outside the utility company, and develop the strategy to trust consumer measurement data. This panel will discuss the challenges and pathways for the development of an ensemble cybersecurity model based on predictive state estimation to detect cybersecurity anomalies in OT network including EMS, ADMS, and DERMS.

cybersecurity↗
DOE OSTI2023

Maximum-impact Adversary Design for Network-based Control System: A Case Study on Grid-interactive Efficient Buildings

The Internet of Things (IoT) technology has dramatically improved the efficiency of today's building operation and management. By connecting controllable devices into a communication network, control signals can be easily passed to the devices, and operating status can be acquired from measurable ends with minimal effort. However, this all-connected configuration could also expose the network-based control system (NBCS) to malicious actions, such as cyberattacks. One of the common NBCSs is the building automation system. With the promotion of grid-interactive efficient buildings (GEBs), there has been increasing attention on securing the buildings from the network perspective. This research proposes a maximum-impact adversary design framework so that the adversary can provide the most adversarial impact on the controlled system while remaining stealthy. The proposed framework is numerically demonstrated on a network-based building energy and control system. The building energy system is built in a Modelica-based simulation environment and controlled by the state-of-the-art ASHRAE Guideline 36 control sequences. The control commands at the supervisory level, generated from the Guideline 36 controller, are assumed to be sent to local devices through communication networks using the BACnet protocol. Simulation results show that the proposed maximum-impact adversary on such a system can stealthily affect the building system's performance to its maximum extent. It is anticipated that results can be used by researchers and practitioners in the building automation industry to design efficient and robust cyber-attack detection algorithms, especially for stealthy attacks.

Chu, Mengyuan↗
DOE OSTI2023

Robust and cybersecure coordinated unintentional island detection for microgrids

Unintentional islanding (UI) of a circuit of distributed energy resources (DERs) may leave area electrical power systems (EPS), external to the DER circuit, energized. Thus, UI detection methods have been developed to detect unintentional islanding and trigger a UI response. However, individual UI detection methods have various deficiencies. Thus, a consensus-based UI detection process is disclosed that builds a consensus from multiple UI detection sources, optionally implementing different UI detection methods. The redundancy in this consensus-based UI detection process provides robust, sensitive, selective, and cybersecure UI detection for the entire DER circuit. For example, the consensus-based UI detection process may eliminate or reduce non-detection zones, avoid false positives, thwart cyber-attacks, and/or the like.

Brissette, Alex↗