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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessing Anomaly-Based Intrusion Detection Configurations for Industrial Control Systems

To reduce cost and ease maintenance, industrial control systems (ICS) have adopted Ethernetbased interconnections that integrate operational technology (OT) systems with information technology (IT) networks. This integration has made these critical systems vulnerable to attack. Security solutions tailored to ICS environments are an active area of research. Anomalybased network intrusion detection systems are well-suited for these environments. Often these systems must be optimized for their specific environment. In prior work, we introduced a method for assessing the impact of various anomaly-based network IDS settings on security. This paper reviews the experimental outcomes when we applied our method to a full-scale ICS test bed using actual attacks. Our method provides new and valuable data to operators enabling more informed decisions about IDS configurations.

Gillen, Rob↗
NASA NTRS2001

Adapting safety requirements analysis to intrusion detection

Several requirements analysis techniques widely used in safety-critical systems are being adapted to support the analysis of secure systems. Perhaps the most relevant system safety techique for Intrusion Detection Systems is hazard analysis.

requirements analysis safety intrusion detection↗
DOE OSTI2023

Assessing Methodologies for Detecting Water Intrusion in Wall Systems: Phase 2

Studies by the University of Florida, the Environmental Protection Agency (EPA) and the U.S. Department of Housing (HUD) have revealed that there is a substantial fraction of commercial and residential buildings that have been exposed to moisture resulting in damage or durability problems. Water intrusion into building envelope components leads to a variety of undesirable conditions such as mold, wood rot, corrosion, and aesthetic damage. Tests methods that are presently used to evaluate the amount of water intrusion into a building envelope component are usually qualitative in nature. For example, ASTM E 331, Standard Test Method for Water Penetration of Exterior Windows, Curtain Walls, and Doors by Uniform Static Air Pressure Difference requires that you “observe and record points of water leakage, if any.” This test was originally developed to assess the performance of fenestration products but is commonly adapted to evaluate other enclosure assemblies. However, when it is typically used for walls, this procedure is limited to recognizing if the moisture is visually observable from the backside side of the sheathing. It does not address moisture that is absorbed in the layers of the building envelope component, which could impact the durability of the assembly. Clearly a quantitative means of determining water penetration would improve the quality of this type of test and assist with better understanding the resultant impact on enclosure assemblies. In 2018-20, Oak Ridge National Laboratory, in conjunction with the Air Barrier Association of America, initiated a research project to address this issue. The purpose of that study was to evaluate nine different methods of detecting moisture intrusion through a wall assembly. air and water barrier. The wall assemblies included metal frame construction faced with gypsum sheathing and both self-adhered and fluid applied air and water barriers (AWB) were evaluated for this exercise. This project did not test the efficacy of the different AWBs, rather, fasteners were purposely installed in various ways to foster water penetration and activate the different methods of detection. Each detection method was evaluated for five features that included simplicity of use, cost of implementation, whether the method was quantitative or subjective, accuracy, and applicability. A scale of green/yellow/red was used to assess each feature where green was acceptable, yellow was borderline, and red was not to be pursued at this time. This report covers additional research that has been undertaken to extend the activities initiated in this earlier project with refinements for specific detection methods and considerations for expansion related to field versus laboratory testing standards.

42 ENGINEERING↗
DOE OSTI2023

Designing an Intrusion Detection for an Adjustable Speed Drive System Controlling a Critical Process

In this article, we address the cyber-security problem of industrial control systems (ICSs) when their sensor measurements may be compromised due to an attacker who has intercepted those measurements via a network. We introduce a general-purpose method “Dynamic Watermarking (DW)” to detect potential cyber-intrusions on speed sensor measurements within industrial control systems, which deploy an adjustable speed drive (ASD) to control a critical process. The DW method is injecting a random private low-amplitude signal with a zero mean Gaussian distribution, “watermark”, into one of the input phase voltages powering the ASD system. The watermark signal propagates through the system including pulse width modulation (PWM) power conversion stage and motor, then ultimately appears in the speed sensor measurements. By deploying two statistical DW tests with two proper thresholds, the system can detect potential cyber-intrusions or unobservable cyber-attacks such as replay attacks and false data injection attacks (FDIA). The DW method tested on a laboratory-scale ASD system experimentally to protect the system against cyber-intrusions. This system, powered by a commercial PWM drive operating at 208 V, 3-phase, and 3.7 kW, served as our experimental platform.

42 ENGINEERING↗
DOE OSTI2021

Anonymization of Network Traces Data through Condensation-based Differential Privacy

Network traces are considered a primary source of information to researchers, who use them to investigate research problems such as identifying user behavior, analyzing network hierarchy, maintaining network security, classifying packet flows, and much more. However, most organizations are reluctant to share their data with a third party or the public due to privacy concerns. Therefore, data anonymization prior to sharing becomes a convenient solution to both organizations and researchers. Although several anonymization algorithms are available, few of them allow sufficient privacy (organization need), acceptable data utility (researcher need), and efficient data analysis at the same time. This article introduces a condensation-based differential privacy anonymization approach that achieves an improved tradeoff between privacy and utility compared to existing techniques and produces anonymized network trace data that can be shared publicly without lowering its utility value. Our solution also does not incur extra computation overhead for the data analyzer. A prototype system has been implemented, and experiments have shown that the proposed approach preserves privacy and allows data analysis without revealing the original data even when injection attacks are launched against it. When anonymized datasets are given as input to graph-based intrusion detection techniques, they yield almost identical intrusion detection rates as the original datasets with only a negligible impact.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Advanced Grid Operational Technology Edge-Level Threat Detection

This report presents a deployable solution to improve the cybersecurity situational awareness of the legacy SCADA system infrastructure in power grids. The main goal of this project is to provide system owners and operators a highly trusted, intelligent alarm system and comprehensive situational awareness of ongoing or potential cybersecurity threats on the grid network. The key contributions of this project include: (1) the development of software, the Intrusion Detection Visualizer for the Operational Technology Network (IViz-OT), to visualize and locate intrusions on the grid network; (2) testing the signature-based Hybrid Intrusion Detection for Energy Systems (HIDES) for different types of intrusions; (3) the integration of HIDES and IViz-OT into the visualization dashboard; and (4) real-time testing using a hardware-in-the-loop test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

On the Limits of EM Based Detection of Control Logic Injection Attacks In Noisy Environments

The difficulty in applying traditional security mechanisms in Industrial Control System (ICS) environments makes a large portion of these mission-critical assets vulnerable to cyber attacks. Therefore, there is a dire need for the development of novel security mechanisms specifically designed to protect such critical systems. Recently a lot of attention has been given to mechanisms that exploit the EM emanations of devices for defense purposes. Such practices may lead to the development of robust external and non-intrusive anomaly detection systems. Nevertheless, the majority of current work in the area neglects to consider the implications of real-life environments, particularly environmental noise. In this work, we explore the limits of EM-based anomaly detection towards identifying injection attacks in control logic software in noisy environments. Our study conducted upon both synthetically generated and real signals identified that indeed environmental noise might significantly degrade the accuracy of the anomaly detection process. Experiments done upon synthetic data indicated that assuming that signals are captured with high sampling rates, even minor code injections can be detected with above-90% accuracy in noisy environments where SNR is up to -2dB. This is true even if naive detection methods are considered. Moreover, experiments done using a real-life testbed attest that even single-instruction injections can be detected with near-perfect accuracy in relatively clean environments. Finally, noise-elimination techniques can drastically improve the reliability of the detection mechanism even in noisy environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Blockchain based Communication Architectures with Applications to Private Security Networks

Existing communication protocols in high consequence security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be destroyed or interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing two types of data input: visual imagers and microwave sensor information. These data types are ubiquitous in perimeter intrusion detection security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm to nd important targets in the scene. The raw data from the camera and the outputs from the detection algorithm are then placed in a transaction on the distributed ledger. Similarly, microwave data is used to detect relevant events and are placed in a transaction. These transactions are then bundled into blocks and broadcast to the rest of the network using the Bitcoin-based MultiChain protocol. We develop five tests to examine the security metrics of our network. We performed the five security metric test using different sized networks from 7 to 39 nodes to determine how the metrics scale with respect to size. We nd that when compared to a centralized architecture our implementation provides a resiliency increase that is expected from a blockchain-based protocol without slowing the system so much that a human operator would notice. Furthermore, our approach is able to detect tampering in real time. Based on these results, we theorize that security networks in general could use a blockchain-based approach in a meaningful way.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Artificial Intelligence for Energy Systems Cybersecurity

Artificial intelligence and machine learning systems have the potential to influence the future design and implementation of cybersecurity systems for the power grid. These systems may enhance the overall operation of the power system by leveraging and making sense of massive amounts of data. However, we must also understand how AI/ML will need to be protected from cyber threat actors. We discuss the existing insights the NREL team has developed using AI/ML systems and then present resources including ESIF and the Cyber Energy Emulation Platform that can be used to generate training data and insights. We end by offering suggestions on priority research paths for AI in cybersecurity.

artificial intelligence↗
DOE OSTI2022

General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization

Distinguishing malicious anomalous activities from unusual but benign activities is a fundamental challenge for cyber defenders. Prior studies have shown that statistical user behavior analysis yields accurate detections by learning behavior profiles from observed user activity. These unsupervised models are able to generalize to unseen types of attacks by detecting deviations from normal behavior, without knowledge of specific attack signatures. However, approaches proposed to date based on probabilistic matrix factorization are limited by the information conveyed in a two-dimensional space. Non-negative tensor factorization, on the other hand, is a powerful unsupervised machine learning method that naturally models multi-dimensional data, capturing complex and multi-faceted details of behavior profiles. Herein, our new unsupervised statistical anomaly detection methodology matches or surpasses state-of-the-art supervised learning baselines across several challenging and diverse cyber application areas, including detection of compromised user credentials, botnets, spam e-mails, and fraudulent credit card transactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

DER Translate

SAND2024-13723O This software translates and maps any .xlsx-based distributed energy resource (DER) device from the SunSpec certification registry (https://sunspec.org/certified-registry/) to a JSON-based DER models map. It is then read by DER monitoring tools for applications such as network intrusion detection and system health monitoring. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fragkos, Georgios↗
DOE OSTI2026

Securing The Future: 2026 Manufacturing & Critical Infrastructure Threat Landscape

This report outlines the current state of manufacturing weaknesses introduced by the complexities of modern environments, including cloud services and Internet of Things (IoT) devices, with particular attention paid to the unique vulnerabilities encountered by SMMs. It also highlights CyManII’s strategic initiatives and collaborative solutions to mitigate these risks and strengthen the cybersecurity posture of the manufacturing ecosystem. Utilizing data from 2025 to inform forward-looking mitigation strategies, this report provides manufacturers with a clear understanding of both current and emerging cybersecurity threats, as well as practical opportunities to strengthen their cyber ecosystems. The following sections detail key vulnerabilities and threat vectors, along with actionable mitigation strategies, many of which have been developed or piloted through CyManII-led efforts. A thorough understanding of these risks and mitigation strategies is essential for manufacturers seeking to strengthen the security and resilience of their manufacturing operations.

3D Printing↗
DOE OSTI2020

CEEP (Cyber-Energy Emulation Platform) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Vaughan, Evan↗
DOE OSTI2022

Cyber Energy Emulation Platform (CEEP) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Rivera, Joshua↗
NASA NTRS2002

Speaking Volumes About 3-D

In 1999, Genex submitted a proposal to Stennis Space Center for a volumetric 3-D display technique that would provide multiple users with a 360-degree perspective to simultaneously view and analyze 3-D data. The futuristic capabilities of the VolumeViewer(R) have offered tremendous benefits to commercial users in the fields of medicine and surgery, air traffic control, pilot training and education, computer-aided design/computer-aided manufacturing, and military/battlefield management. The technology has also helped NASA to better analyze and assess the various data collected by its satellite and spacecraft sensors. Genex capitalized on its success with Stennis by introducing two separate products to the commercial market that incorporate key elements of the 3-D display technology designed under an SBIR contract. The company Rainbow 3D(R) imaging camera is a novel, three-dimensional surface profile measurement system that can obtain a full-frame 3-D image in less than 1 second. The third product is the 360-degree OmniEye(R) video system. Ideal for intrusion detection, surveillance, and situation management, this unique camera system offers a continuous, panoramic view of a scene in real time.

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