SEARCH · Search NASA

Results for “Network Security Quality”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Summer 2024 INL Intern Poster Session Submission - Brian Schumitz

This LRS submission is my poster for the INL Intern Poster Session, Summer 2024. Abstract: The Software Engineering and Cybersecurity Lab (SECL) at Montana State University has developed PIQUE, a system for evaluating software quality. PIQUE's adaptability allows for language-specific static-analysis operations, including a model for assessing cloud microservice ecosystems. These ecosystems often rely on Docker for efficient deployment and management of containerized services. Our research focuses on evaluating the network quality within these microservice ecosystems. To automate this process, we're utilizing Snort, an open-source intrusion detection system renowned for its ability to detect and log network traffic. By leveraging Snort's customizable rules, we aim to construct comprehensive testing methods for measuring and quantifying the network quality based on traffic between Docker containers. This research aims to enhance the overall security and reliability of cloud microservice ecosystems by providing automated and robust quality evaluation mechanisms, ultimately contributing to the advancement of software engineering practices in these environments

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

DATASET RELEASE AND QUALITY CONTROL REVIEW OF LIVERMORE NEVADA NETWORK (LNN) RECORDINGS OF A SUBSET OF NEVADA NUCLEAR SECURITY SITE NUCLEAR EXPLOSIONS FROM 1979 TO 1992.

Geophysical research on historical nuclear tests is an important aspect of future monitoring capabilities in seismic research. This research is challenging due to the limited number of digital seismic recordings during the peak of nuclear testing (1945-1992). These limited records are unique and non-reproducible data with potential high research impact. Releasing available nuclear explosion seismic records to the explosion monitoring community is thus of high value and is the motivation for this dataset release. The target of this effort was on compilation and quality control of regional seismic records of nuclear explosions recorded on Lawrence Livermore National Laboratory stations ELK, KNB, LAC, and MNV, known collectively as the Livermore National Network (LNN) (Figure 1). LNN was established in the early 1960s for the primary purpose of monitoring underground nuclear testing at the former Nevada Test Site (NTS), now known as the Nevada Nuclear Security Site (NNSS) following the signing of the Limited Test Ban Treaty (LTBT). LNN consisted initially of short-period vertical component Benioff’s recorded on film located at Mina, NV (MNV) and Kanab, Utah (KNB). LNN added two additional stations at Landers, CA (LAC) and Elko, NV (ELK) in 1967 and upgraded equipment to broadband seismometers recorded on frequency modulation (FM) tapes from 1967-1979, followed by digital recordings after 1979 (Jarpe, 1989). The digital recordings were on a variety of now obsolete media, including 9-track, Exabyte, and DAT tapes. Jarpe (1989) describes the seismic station instrumentation details over the period of deployment. LNN recorded valuable non-repeatable unique data of several hundreds of nuclear explosions at NNSS, as well as earthquakes and chemical and mining explosions (Walter, 2020). The details of these nuclear tests are provided in the Department of Energy Report NV-209 Rev 16 (DOE, 2015).

58 GEOSCIENCES↗

DOE OSTI2020

Overview of the MCNP6® SQA Plan and Requirements [Memorandum]

For all X Computational Physics Division (XCP) software under the Associate Laboratory Directorate for Weapons Physics (ALDX), the Weapons Research Services Secure Networks and Assurance Group (WRS-SNA) manages the software quality assurance (SQA) plan, requirements and guidance with respect to development processes and tools to meet the broader LANL SQA requirements. Each XCP software product is categorized into one of three software types: Safety Software, Non-Safety Risk Significant Software, and Non-Safety Commercially Controlled Software. In 2018, using LANL Form 2033, the MCNP6 code was categorized by the XCP division as Non-Safety Commercially Controlled Software, provided in Appendix A. Using WRSFORM- 0001U, the MCNP6 code was graded as a Medium Impact software product, provided in Appendix B. Given these determinations, the WRS-AD-0010U SQA plan is followed for all MCNP6 developments, documentation and code releases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Clean Cities Coalitions: Advancing Affordable, Efficient, and Clean Transportation Fuels and Technologies

This fact sheet provides an overview of the U.S. Department of Energy's (DOE's) Vehicle Technologies Office Clean Cities Coalition Network, which boosts the country's economic vitality, energy security, and quality of life by advancing the deployment of affordable, efficient, and clean transportation fuels and technologies. Coalitions provide the technical expertise local decision makers and fleets need to understand and implement alternative and renewable fuels, electric vehicles, idle-reduction measures, fuel economy improvements, new mobility choices, and emerging transportation technologies.

accomplishments↗

DOE OSTI2020

Y-12 Groundwater Protection Program Monitoring Well Inspection and Maintenance Plan

This plan describes the systematic approach for: inspecting the physical condition of monitoring wells at Y-12, determining maintenance needs that extend the life of a well, and identifying those wells that no longer meet acceptable monitoring well design or well construction standards and require plugging and abandonment. The inspection and maintenance of groundwater monitoring wells is one of the primary management strategies of the Y-12 Groundwater Protection Program (GWPP) Management Plan, that is, the “proactive stewardship of the extensive monitoring well network at Y-12" (Consolidated Nuclear Security, L.L.C. [CNS], 2018). Effective stewardship, and a program of routine inspections of the physical condition of each monitoring well, ensures that representative water-quality samples and hydrologic data are obtained from the well network and protects the subsurface environment. In accordance with the Y-12 GWPP Monitoring Optimization Plan (MOP) for Groundwater Monitoring Wells at the Y-12 National Security Complex, Oak Ridge, Tennessee (CNS, 2017), the status designation (active or inactive) for each well determines the scope and extent of well inspections and maintenance activities. This plan, in conjunction with the above document, formalizes the GWPP approach to focus available resources on monitoring wells which provide the most useful data, and for that reason the GWPP inspects and performs maintenance on the wells sampled by the GWPP. This plan applies to groundwater monitoring wells installed at Y-12 and the related waste management facilities located within the three hydrogeologic regimes: (1) the Bear Creek Hydrogeologic Regime (Bear Creek Regime), (2) the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and (3) the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek Regime encompasses the section of Bear Creek Valley (BCV) immediately west of Y-12. The East Fork Regime encompasses most of the Y-12 process, operations, and support facilities in BCV west of Scarboro Road. The Chestnut Ridge Regime is directly south of Y-12 and encompasses a section of Chestnut Ridge that is bounded to the west by a surface drainage feature (Dunaway Branch, located immediately west of Industrial Landfill II) and by Scarboro Road to the east. The GWPP maintains an extensive database of geographic and construction details and related information for the monitoring wells in each hydrogeologic regime in the Updated Subsurface Database for Bear Creek Valley, Chestnut Ridge, and Parts of Bethel Valley on the U.S. DOE Oak Ridge Reservation (CNS, 2019). A detailed description of the hydrogeologic framework at Y-12 can be found in the GWPP Management Plan (CNS, 2018).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Service-Based, Segmented, 5G Network-Based Architecture for Securing Distributed Energy Resources: Preprint

As the number of connected devices in the energy grid increase exponentially, so too are the cybersecurity risks. With the development of modern communications standards such as 5G and beyond the extent to which devices will continue to connect will continue to increase exponentially along with the inherent risks. However, 5G also includes features to help address cybersecurity concerns and therefore helping to mitigate many of these risks. This paper proposes a new service-based network architecture implementing network-slicing capabilities for connected systems and devices to improve performance, availability, security, and reliability of the grid devices and services. This paper considers the quality of service requirements and criticality of services needed for securely monitoring, operating, and securing Distributed Energy Resource (DER) devices. From developed use cases, network slicing is implemented based on these requirements and resource allocations. This work then highlights examples of how slicing can help prevent standard existing attack methods such as a denial-of-service or similar attack which limits resource availability and network bandwidth to the service and thus limiting its ability to affect other services by misbehaving. The designed network architecture use case will be further tested on a local virtualized testbed to verify secure operation and availability of services. Using hardware-in-the-loop devices and systems on this local testbed, this fully segmented, secure network may be realized and evaluated. Finally, this paper presents the results of this testing.

5G↗

DOE OSTI2023

Clean Cities Coalitions: Advancing Affordable, Efficient, and Clean Transportation Fuels and Technologies

A collaborative network of more than 75 Clean Cities coalitions boosts the country's economic vitality, energy security, and quality of life by advancing the deployment of affordable, efficient, and clean transportation fuels and technologies. Coalitions provide the technical expertise local decision makers and fleets need to understand and implement alternative and renewable fuels, electric vehicles, idle-reduction measures, fuel economy improvements, new mobility choices, and emerging transportation technologies.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Clean Cities Coalitions: Advancing Affordable, Efficient, and Clean Transportation Fuels and Technologies

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Multi-layered Resilient Microgrid Networks

Distribution grid resilience, especially when the grid is under high penetration of Distributed Energy Resources (DER), e.g. PV and energy storage, is essential to ensure the quality of electric power services. The resiliency aspect is particularly important for critical loads that typically include hospitals, police/fire stations, and national security facilities. Networks of multiple interconnected reconfigurable microgrids help to increase renewable energy penetration and may be used as basic building blocks for implementing future resilient power grids. However, this integration requires additional layers of communications, both horizontal and vertical, which may substantially increase the potential cyber attack surfaces as well as escalate risks for wide-spread malfunctions of automation systems. The Mulit-layered Resilient Microgrid Networks project is an industry-academic collaboration between ABB, Duke Energy and the University of Illinois at Urbana-Champaign (UIUC) that has developed and demonstrated a cyber-physical resilient control and communication architecture for deployment of multiple microgrid networks, as well as retrofitting the existing distribution grids by increasing DER penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Data-Informed Synthetic Networks of Water Distribution Systems for Resilience Analysis in Puerto Rico

The increasing potential of infrastructure disruptions calls for high-quality infrastructure models to be used in resilience analysis and decision making. Unfortunately, many utilities and communities do not have access to accurate and detailed models due to a lack of data and resources. Furthermore, security restrictions on sharing infrastructure models present roadblocks to research, analysis, and decision making. Recent advances in the development of synthetic water distribution models provide a potential solution to this problem. There is an opportunity to improve these methods by leveraging incomplete pipe datasets to aid synthetic network generation. To address this gap, we developed a methodology for synthetic network generation that incorporates partial pipe data using a modification of the minimum cost flow algorithm for network generation and pipe sizing. This methodology demonstrates how partial pipe data can be leveraged to improve site-specific synthetic network generation. For the study area of Mayagüez, Puerto Rico, a synthetic model generated using 50% of real pipe data matches the pressure of the validation system with an average error of 23.5 m of head, which improves upon the average error of 31.6 m of head produced by a synthetic model generated using no data of the real pipes. Additionally, synthetic networks are shown to replicate the pressure response under a disruption scenario of the validation network, suggesting potential use in resilience analysis.

resilience analysis↗

DOE OSTI2026

Energy Systems Integration Facility Stewardship Summary: Fiscal Year 2025

A summary of NLR's stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, capability upgrades, and examples of R&D impact. 2025 brought a national focus on energy and ESIF is meeting the moment. All eyes are on data centers and domestic manufacturing and bringing the benefits of artificial intelligence to power system planning and operations. In step with national priorities, ESIF is building out capabilities that advance secure, reliable, and affordable power. ESIF hosted 190 multidisciplinary research projects, 855 high-performance computer users, and collaborated with 81 partners from industry, academia, research, and federal agencies. These research projects resulted in an AI method for detecting high-impedance faults with 90% accuracy, a grid controls demonstration in Connecticut, power quality validation of CorePower's flagship inductor, and a cybersecurity assessment of potential rogue capabilities in digitally connected energy devices. Facility infrastructure improvements enhanced the thermal research network, the SCADA system, the cyber range, power hardware-in-the-loop testing, and more. With support from the U.S Department of Energy (DOE), the ESIF laboratories continue to deliver leading solutions for secure, reliable, and affordable power.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Characterizing Vulnerabilities Associated with Connected Lighting: Exploring Authorization Protocols

Cities are upgrading their infrastructure and converting traditional indoor and outdoor luminaires to Connected Lighting Systems equipped with sensors in an aggressive effort to reduce energy consumption, increase sustainability, and improve the quality of life. When you take something seemingly benign like a lighting system and connect it to the internet, if improperly secured a potential attack vector for hackers is created. Hackers could then access sensitive information, pivot into other networks, shut down services, or enslave devices to do their bidding. In attempt to close this attack vector and secure these systems, this paper extends previous work that investigated, compared and contrasted authentication vulnerabilities in Connected Lighting Systems that identified the need for additional testing and improved test method documentation. One additional authentication test and four new authorization tests were developed utilizing the Open Web Application Security Project (OWASP) as a test development and documentation guide. The new tests were integrated with the previous work to develop an updated test method with a focus on describing test procedures to make them easy to understand and repeat. In addition, a first Connected Lighting System use case was established to begin developing threat profiles that will aid in the identification of vulnerabilities whose focus areas extend beyond authentication and authorization. This use case describes the generation and flow of CLS data which assists in specifying methods to harden CLSs from outside interference and exploitation that can be implemented immediately on existing CLSs and as new products come to market.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

How Low Can You Go? Using Synthetic 3D Imagery to Drastically Reduce Real-World Training Data for Object Detection

Deep convolutional neural networks (DCNNs) currently provide state-of-the-art performance on image classification and object detection tasks, and there are many global security mission areas where such models could be extremely useful. Crucially, the success of these models is driven in large part by the widespread availability of high-quality open source data sets such as Image Net, Common Objects in Context (COCO), and KITTI, which contain millions of images with thousands of unique labels. However, global security relevant objects-of-interest can be difficult to obtain: relevant events are low frequency and high consequence; the content of relevant images is sensitive; and adversaries and proliferators seek to obscure their activities. For these cases where exemplar data is hard to come-by, even fine-tuning an existing model with available data can be effectively impossible. Recent work demonstrated that models can be trained using a combination of real-world and synthetic images generated from 3D representations; that such models can exceed the performance of models trained using real-world data alone; and that the generated images need not be perfectly realistic (Tremblay, et al., 2018). However, this approach still required hundreds to thousands of real-world images for training and fine tuning, which for sparse, global security-relevant datasets can be an unrealistic hurdle. In this research, we validate the performance and behavior of DCNN models as we drive the number of real-world images used for training object detection tasks down to a minimal set. We perform multiple experiments to identify the best approach to train DCNNs from an extremely small set of real-world images. In doing so, we: Develop state-of-the-art, parameterized 3D models based on real-world images and sample from their parameters to increase the variance in synthetic image training data; Use machine learning explainability techniques to highlight and correct through targeted training the biases that result from training using completely synthetic images; and Validate our results by comparing the performance of the models trained on synthetic data to one another, and to a control model created by fine-tuning an existing ImageNet-trained model with a limited number (hundreds) of real-world images.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Network Slicing for Federated Learning in Operational Technology Environment

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) environments are essential to modern infrastructure, facing challenges in ensuring low-latency, high-throughput communication while mitigating cyber threats. This paper presents a framework integrating Federated Learning (FL) and network slicing with Quality of Service (QoS) to enable real-time monitoring without disrupting OT operations. Leveraging digital twin technology and Network Function Virtualization (NFV), the architecture supports predictive analytics and Industry 4.0 requirements. FL facilitates decentralized model training, preserving data privacy and scalability, though it introduces potential throughput constraints. Network slicing addresses this by creating dedicated virtualized segments optimized for performance and security. Advanced fault tolerance at the container and instance levels enhances system reliability. The proposed architecture ensures high throughput, low latency, and secure orchestration for real-time anomaly detection in OT networks. Performance evaluations validate its efficiency in throughput, deployment, and learning accuracy, providing a robust foundation for future ICS automation and data-driven decision-making.

Delgado, Brian G. Rodiles [University of Texas at ↗

DOE OSTI2020

Quantifying Graph Uncertainty from Communication Data

Graphs are a widely used abstraction for representing a variety of important real-world problems including emulating cyber networks for situational awareness, or studying social networks to understand human interactions or pandemic spread. Communication data is often converted into graphs to help understand social and technical patterns in the underlying communication data. However, prior to this project, little work had been performed analyzing how best to develop graphs from such data. Thus, many critical, national security problems were being performed against graph representations of questionable quality. Herein, we describe our analyses that were precursors to our final statistically grounded technique for creating static graph snapshots from a stream of communication events. The first analyzes the statistical distribution properties of a variety of real-world communication datasets generally fit best by Pareto, log normal, and extreme value distributions. The second derives graph properties that can be estimated given the expected statistical distribution for communication events and the communication interval to be viewed node observability, edge observability, and expected accuracy of node degree. Unfortunately, as that final process is under review for publication, we can't publish it here at this time.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Wildfires increasingly impact western US fluvial networks

Wildfires are increasing globally in frequency, severity, and extent, but their impact on fluvial networks, and the resources they provide, remains unclear. We combine remote sensing of burn perimeter and severity, in-situ water quality monitoring, and longitudinal modeling to create the first large-scale, long-term estimates of stream+river length impacted by wildfire for the western US. We find that wildfires directly impact ~6% of the total stream+river length between 1984 and 2014, increasing at a rate of 342 km/year. When longitudinal propagation of water quality impacts is included, we estimate that wildfires affect ~11% of the total stream+river length. Our results indicate that wildfire activity is one of the largest drivers of aquatic impairment, though it is not routinely reported by regulatory agencies, as wildfire impacts on fluvial networks remain unconstrained. We identify key actions to address this knowledge gap and better understand the growing threat to fluvial networks, water security, and public health risks.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Best Practices for Grid Communications

As the grid evolves, the communications architecture will need to evolve with it. That architecture affords a structured means by which the evolving complexities of the modern electric grid can be managed. This document provides best practices that can be implemented in the grid of today and evolve towards the grid and grid architecture of the future. The evolving grid and its control communications increasingly rely on commercial communications providers and a variety of technologies, from wireless (e.g., 5G, microwave, Wi-Fi) to wireline (fiber, copper) to radio communications (P25, other repeater-based systems), and all these communications systems rely on electric power. A reliable and resilient grid must account for this complex set of interdependencies in its planning activities, especially those involving restoration and recovery. The participation of all relevant parties in both planning and exercising of plans can prevent unexpected conditions that impede the reliable operation and recovery of the grid. Best practices for grid communications include using a Network Management System to document the operational state, define and monitor baselines, detect changes, and accelerate response to abnormalities. If transitioning from SONET to IP/packet-based systems, translating grid requirements into communications requirements for latency, bandwidth and throughput, IP packet delay variation, packet loss, and availability should inform and drive technology planning and selection as well as that communication system’s Quality of Service (QoS) policies and Service Level Agreements (SLAs). Secure and reliable timing is another key component of a reliable and resilient grid that can operate through adverse events. A trusted internal NTP configuration, an integrated and diverse timing delivery system, optimizing the timing architecture based on the transport technologies of the communications system, and using established standards can deliver the level of timing accuracy required by a range of time-sensitive power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Smart Packaging for Critical Energy Shipment (SPaCES)

Recent technical advances have brought forth revolutionary Smart Packaging (SP) technology. SP incorporates multiple electronics, chemical, and mechanical sensing technologies into packaging materials, and utilizes them to monitor and display package content status. SP can also employ embedded micro actuators to react to undesirable package conditions such as moisture/temperature anomalies or harmful chemical reactions and neutralize it. When further integrated with wireless sensing and secure networking, SP provides wholistic system-wide remote situation awareness capability for real-time crisis management. Finally, we also see that SP can be further integrated with 3D printing technology to offer form-factor customization and application specific solutions suitable for DOE (Department of Energy) NNSA’s (National Nuclear Security Administration) R/N (radiological/nuclear) material shipment and management needs; this has the potential to improve safety, security, and overall operation process quality. This report surveys SP technology as the state of the art (SOTA) and analyzes how it can integrate with cybersecurity and 3D printing to address NNSA’s critical R/N material shipment and storage requirements. This report further presents our FY23/24 investigation plan describing project background, goal, motivation, proposed work, and statement of work and cost.

47 OTHER INSTRUMENTATION↗