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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CCE Case Study: Baltavia Substation Power Outage

In this case study, we will examine a fictional event broadly inspired by the real power outages in Ukraine that took place in December 2015 and December 2016—both the result of cyber-enabled sabotage. The actual events of 2015 and 2016 were well-documented—the adversaries in these attacks gained access to a few power companies’ corporate networks, pivoted to industrial control system (ICS) networks, and created widespread physical effects in the form of power outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2021

Cybersecurity for Electric Vehicle Fast-Charging Infrastructure

The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Cybersecurity for Electric Vehicle Fast-Charging Infrastructure: Preprint

The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Cybersecurity for Fast Charging EV Infrastructure

The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2024

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗
DOE OSTI2022

Synchrophasors-based Master State Awareness Estimator for Cybersecurity in Power Grid: Testbed Implementation & Field Demonstration

The integration of distributed energy resources(DERs) and expansion of complex network in the distribution grid requires an advanced distributed state estimator to monitor the grid health at micro-level. The distribution state estimator will improve the situational awareness and resiliency of distributed power system. This paper proposes a synchrophasors-based master state awareness (MSA) estimator to enhance the cybersecurity in distribution grid by providing a real-time estimation of system operating states to control center operators. In this paper, the proposed MSA estimator utilizes only phasor measurements, bus magnitudes and angles, from phasor measurement units (PMUs),deployed in local substations, to estimate the system states and also detects data integrity attacks, such as load tripping attack that disconnects the load. To validate the proof of concept, we implement the proposed methodology in cyber-physical testbed environment at the Idaho National Laboratory (INL) Electric Grid Security Testbed. Further, to address the “valley of death” and support technology commercialization, field demonstration is also performed at the Critical Infrastructure Test Range Complex(CITRC) at the INL. Our experimental results reveal a promising performance in detecting load tripping attack and providing an accurate situational awareness through an alert visualization dashboard in real-time

42 ENGINEERING↗
DOE OSTI2022

Aggregate attack surface management for network discovery of operational technology

Interconnectivity has become a substratum of technology as the benefits of data-driven functionality are being realized in nearly all industries. Increased connectivity of Operational Technology (OT) exacerbates cyber risks because Industrial Control Systems (ICS) are becoming exposed to the Internet. These exposures are often done inadvertently through misconfigurations as additional network devices come online. Attack surface management (ASM) platforms can be used to identify vulnerabilities by performing external network discovery over the Internet using web spiders. These web spiders enable big data analytics of Internet of Things (IoT) devices as identifiable information of Internet-exposed equipment are archived in searchable databases that are made publicly available. There are a multitude of ASM service providers on the market. Here, this study was conducted to evaluate several commonly known tools to determine the aggregate attack surface of control systems. Queries were crafted by targeting commonly known manufacturers and communication protocols found in OT networks. Identified devices were that categorized based on technology types. Each query was replicated between several tools to target identical ICS equipment. Findings in this paper suggested a significant variance in the exposures discovered by each tool, but unique contributions were identified for each tool when a merged attack surface was derived. Therefore, all tools should be used in aggregate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CCE Case Study: Baltavia Substation Power Outage

In this case study, we will examine a fictional event broadly inspired by the real power outages in Ukraine that took place in December 2015 and December 2016 - both the result of cyber-enabled sabotage. The actual events of 2015 and 2016 were well-documented - the adversaries in these attacks gained access to a few power companies’ corporate networks, pivoted to industrial control system (ICS) networks, and created widespread physical effects in the form of power outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Disrupting EV Charging Sessions and Gaining Remote Code Execution with DoS, MITM, and Code Injection Exploits using OCPP 1.6

Open Charge Point Protocol (OCPP) 1.6 is widely used in the electric vehicle (EV) charging industry to communicate between Charging System Management Services (CSMSs) and Electric Vehicle Supply Equipment (EVSE). Unlike OCPP 2.0.1, OCPP 1.6 uses unencrypted websocket communications to exchange information between EVSE devices and an onpremise or cloud-based CSMS. In this work, we demonstrate two machine-in-the-middle (MITM) attacks on OCPP sessions to terminate charging sessions and gain root access to the EVSE equipment via remote code execution (RCE). Second, we demonstrate a malicious firmware update with a code injection payload to compromise an EVSE. Lastly, we demonstrate two methods to prevent availability of the EVSE or CSMS. One of these, originally reported by SaiFlow, prevents traffic to legitimate EVSE equipment using a DoS-like attack on CSMSs by repeatedly connecting and authenticating several CPs with the same identities as the legitimate CP. These vulnerabilities were demonstrated with proof-of-concept exploits in a virtualized Cyber Range at Wright State University and/or with a 350 kW Direct Current Fast Charger (DCFC) at Idaho National Laboratory. The team found that OCPP 1.6 could be protected from these attacks by adding secure shell (SSH) tunnels to the protocol, if upgrading to OCPP 2.0.1 was not an option. Index Terms—Electric vehicle charging, cybersecurity, OCPP, cyberattack, cyber-resilience. INSPEC Accession Number: 23981565

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Experimental Setup for Grid Control Device Software Updates in Supply Chain Cyber-Security

Supply chain cyberattacks that exploit insecure third-party software are a growing concern for the security of the electric power grid. These attacks seek to deploy malicious software in grid control devices during the fabrication, shipment, installation, and maintenance stages, or as part of routine software updates. Malicious software on grid control devices may inject bad data or execute bad commands, which can cause blackouts and damage power equipment. This paper describes an experimental setup to simulate the software update process of a commercial power relay as part of a hardware-in-the-loop simulation for grid supply chain cyber-security assessment. The laboratory setup was successfully utilized to study three supply chain cyber-security use cases.

Keller, Joseph↗
DOE OSTI2025

Virtual Agents-Based Attack-Resilient Distributed Control for Islanded AC Microgrid

Due to its dependence on a communication network, distributed secondary control of microgrids is susceptible to denial-of-service (DoS) attacks in channel shutdown mode, which may negatively impact the network connectivity and thus deteriorate the coordination and power sharing among distributed generators (DGs). Honeypot is a common method for cyber deception by introducing fake targets. However, in the context of microgrid, the misleading information spread by honeypots will also impact the system performance. This paper proposes an attack-resilient distributed control for AC microgrids utilizing virtual agents (VAs) to counteract both DoS edge and node attacks. The VAs are designed to not impact the system’s steady state during normal operation but to share information among neighboring real agents and serve as dummy targets for DoS attacks. The control with VAs is implemented by a primal-dual gradient based distributed algorithm to efficiently obtain a practical solution for voltage/frequency regulation and power sharing. The simulation results on a 4-DG test system and a modified IEEE 34-bus system show that 1) VAs do not impact the normal functionality of the test system, and 2) deploying VAs can enhance the resilience of the microgrid control against DoS edge and node attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗
DOE OSTI2021

Foundations of Rigorous Cyber Experimentation

This report presents the results of the “Foundations of Rigorous Cyber Experimentation” (FORCE) Laboratory Directed Research and Development (LDRD) project. This project is a companion project to the “Science and Engineering of Cyber security through Uncertainty quantification and Rigorous Experimentation” (SECURE) Grand Challenge LDRD project. This project leverages the offline, controlled nature of cyber experimentation technologies in general, and emulation testbeds in particular, to assess how uncertainties in network conditions affect uncertainties in key metrics. We conduct extensive experimentation using a Firewheel emulation-based cyber testbed model of Invisible Internet Project (I2P) networks to understand a de-anonymization attack formerly presented in the literature. Our goals in this analysis are to see if we can leverage emulation testbeds to produce reliably repeatable experimental networks at scale, identify significant parameters influencing experimental results, replicate the previous results, quantify uncertainty associated with the predictions, and apply multi-fidelity techniques to forecast results to real-world network scales. The I2P networks we study are up to three orders of magnitude larger than the networks studied in SECURE and presented additional challenges to identify significant parameters. The key contributions of this project are the application of SECURE techniques such as UQ to a scenario of interest and scaling the SECURE techniques to larger network sizes. This report describes the experimental methods and results of these studies in more detail. In addition, the process of constructing these large-scale experiments tested the limits of the Firewheel emulation-based technologies. Therefore, another contribution of this work is that it informed the Firewheel developers of scaling limitations, which were subsequently corrected.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Radio Frequency Spectrum Audit to Inventory Private Cellular Base Station Infrastructure

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize cellular base stations. Localizing cellular base stations provides various advantages, including information security, cybersecurity, spectrum management, and interference detection. For example, the MITRE ATT&CK® (Adversarial Tactics, Techniques, and Common Knowledge architecture) [1] and Common Attack Pattern Enumeration and Classification [2] emphasize the importance of being able to minimize the cyber security threat presented by unregulated private cellular base stations (PCBS). The majority of published research looks at the malicious use of PCBSs and focuses on using data retrieved from user equipment (UE), data obtained from an application on the UE, or data shared between the UE and a mobile network to locate it. This innovative strategy, however, focuses on the passively discovered uniqueness of radio frequency (RF) transmissions from commercial cellular infrastructure received in a designated monitoring position (DMP).

42 ENGINEERING↗