Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “network security”

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.

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

At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Developing an AI-Powered Zero-Trust Cybersecurity Framework for Malware Prevention in Nuclear Power Plants

This study presents the development of an AI-powered Zero-Trust cybersecurity framework for malware prevention in nuclear power plants. The framework aims to enhance the security of critical systems within nuclear power plants by adopting the principles of Zero-Trust and leveraging artificial intelligence (AI) technologies. By assuming no implicit trust in any user or device and continuously authenticating and authorizing access, the framework ensures a robust defense against malware attacks. The integration of AI allows for the detection and prevention of malware through behavioral analytics, endpoint protection, network segmentation, and continuous monitoring. The paper discusses the key considerations, steps, and technologies involved in developing this framework, emphasizing the importance of regular updates, training, compliance, and auditing. The proposed framework serves as a comprehensive approach to safeguarding nuclear power plants from sophisticated malware threats and protecting the integrity and safety of critical infrastructure.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Spiking Markov Reward Process v.0.1

SAND2024-11150O The Spiking Markov Reward Process software is a spiking neural network that streams binary arithmetic and computes the state value function of a Markov reward process. The software will be released to the SpiNNcloud group for development of neuromorphic acceleration. 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.

Wang, Felix↗
DOE OSTI2024

Defect diffusion graph neural networks (d2gnn)

SAND2025-01004O Defect Diffusion Graph Neural Networks (d2gnn) is a software tool that assists in the discovery of new materials for high-temperature, clean-energy applications. It uses advanced graph neural networks to model the relationship between material structures and their defect properties. The application helps predict how materials will behave under different conditions and accelerates the development of innovative materials. 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.

Witman, Matthew [Sandia National Lab. (SNL-CA), Li↗
NASA NTRSDate not supplied

Tracking and Recovery of the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) Reentry Vehicle (RV)

The LOFTID mission launched from Vandenberg on Nov 10, 2022, and successfully demonstrated the reentry of a 6m diameter inflatable aeroshell from low Earth orbit. This paper will cover the design features implemented to enable recovery of the flight vehicle, and will discuss the splashdown calculations, in-flight tracking, recovery from the ocean, and post-flight inspection of the flight vehicle. To support recovery of the RV and ejected data recorder after splashdown, a recovery ship was pre-positioned near the predicted splashdown ellipse in the Pacific Ocean. The splashdown ellipse was repeatedly updated as launch approached. In-flight tracking included transmission from the RV of GPS data through both the Iridium satellite network and the LoRa direct RF link, along with IR video cameras on the recovery ship and airborne imagery from the SCIFLI Team. Using both the GPS data and the IR imagery, the recovery ship tracked down the RV, and deployed an inflatable boat to approach the RV and attach it to the ship’s crane, after which the RV was hoisted on board and secured in its GSE recovery stand. The ship then tracked down the ejected data recorder, which was also broadcasting its GPS data, and pulled it from the water. Once the ship returned to port, the RV was hoisted ashore for additional inspection, removal of the data recorders, and repackaging for shipment back to NASA Langley.

Robert A. Dillman↗
NASA NTRSDate not supplied

Tracking and Recovery of the LOFTID RV (Low-Earth Orbit Flight Test of an Inflatable Decelerator Reentry Vehicle)

The LOFTID mission launched from Vandenberg on Nov 10, 2022, and successfully demonstrated the reentry of a 6m diameter inflatable aeroshell from low Earth orbit. This paper will cover the design features implemented to enable recovery of the flight vehicle, and will discuss the splashdown calculations, in-flight tracking, recovery from the ocean, and post-flight inspection of the flight vehicle. To support recovery of the RV and ejected data recorder after splashdown, a recovery ship was pre-positioned near the predicted splashdown ellipse in the Pacific Ocean. The splashdown ellipse was repeatedly updated as launch approached. In-flight tracking included transmission from the RV of GPS data through both the Iridium satellite network and the LoRa direct RF link, along with IR video cameras on the recovery ship and airborne imagery from the SCIFLI Team. Using both the GPS data and the IR imagery, the recovery ship tracked down the RV, and deployed an inflatable boat to approach the RV and attach it to the ship’s crane, after which the RV was hoisted on board and secured in its GSE recovery stand. The ship then tracked down the ejected data recorder, which was also broadcasting its GPS data, and pulled it from the water. Once the ship returned to port, the RV was hoisted ashore for additional inspection, removal of the data recorders, and repackaging for shipment back to NASA Langley.

Robert A Dillman↗
DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk Presentation for EnCyCriS

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Engineering Out Industry 4.0 Cyber Risk

The increasing complexity and business requirements of operational technology (OT) devices is beginning to break the normal segmentation between information technology (IT) and OT networks. The introduction of industry 4.0 devices such as industrial internet of things (IIoT) and other intelligent industrial devices (IID), virtualized OT systems, OT cloud integration, and artificial intelligence (AI)-driven industrial control systems (ICS) has challenged traditional IT/OT cybersecurity strategies. Industry 4.0 devices are analyzed through the lens of well-regarded models such as the PERA model and confidentiality, integrity, and availability (CIA) security objectives, showing the division between what is needed and traditional cybersecurity countermeasures. In this paper, the practice of Cyber-Informed Engineering (CIE) is proposed to bridge the gap between IT/OT security, enhance the practice of cybersecurity in this modern age, and reduce the impacts of consequential events in OT.

42 - ENGINEERING↗
DOE OSTI2020

Automated Threat Recognition For Aviation Security Applications

We have developed a framework for automated threat recognition (ATR) of explosive threat materials for both single-energy and dual-energy X-ray CT systems. Under this framework, two different types of ATR have been developed. The first type of ATR employs supervised machine learning with statistical characterization of target materials for threat identification training. The reliance only on statistical characterization information for threat training uniquely enables this style of ATR to adapt quickly to evolving threats. The second type of ATR employs deep learning through convolutional neural networks. Convolutional neural networks are attractive due to their human-like capacity for learning and strong ability to identify trends and patterns. Although this method is more powerful than the first type, it requires large amounts of training data and therefore is less agile. Each ATR performs threat characterization at the voxel neighborhood level. This approach avoids the use of threat shape as a detection criterion, which is prohibited by DHS and TSA guidelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Supporting Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA (Final Report)

As modern power grids tend towards greater levels of automation and communication, the challenges of identifying and mitigating vulnerabilities to cyber-attacks are ones that are increasingly demanding attention. Today’s power system has evolved to form the foundational bedrock of modern society, and an attack on this infrastructure could prove disastrous. In this project we were tasked to investigate the use of distribution synchrophasors as an independent isolated sensor network with which we can corroborate, or flag potentially spoofed,Supervisory Control And Data Acquisition (SCADA) data. We adapted an approach to marry the underlying physical properties of power systems with the network communications used by power systems in order to offer insights unattainable by either data stream isolation. While the concept of intrusion detection systems (IDS) is well understood for monitoring network traffic and traditional IT computing systems, the approach discussed in this report is motivated by several key notions: first, current SCADA communications alone presents an incomplete view of the grid. Second, the power grid, and the equipment controlling it, is grounded by laws of physics. Given this, we leverage high-frequency physical grid measurements to understand the physical condition of the grid, and combine this with SCADA. While high-frequency physical grid measurements and SCADA communication over Internet Protocol (IP) networks are fundamentally disparate information sources, when collectively examined through appropriate lenses, they offer a much more nuanced depiction of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

REDLY

SAND2025-11838O REDLY provides a framework for designing, training, and validating physics-informed neural networks for power system applications. It trains surrogates for Alternating Current Power Flow prediction and general economic dispatch problems, such as Alternating Current Optimal Power Flow and Direct Current Power Flow. 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.

Blakely, Logan↗
DOE OSTI2024

Essence2.0 Development and Deployment (Final Report)

The objective of the project was to take two core technologies that have been developed under the Recipient’s solid laboratory products and integrate them into a single CyberPhysical awareness platform and complete development on current field-tested prototypes that will extend the integrated capability of the platform. During the final development phase, the Recipient development team and its selected industry partners tested and hardened the platform to ensure resilient and secure operation of the integrated platform. The team also executed substantial field testing and established the framework for defining the organization and/or commercial infrastructure needed to sustain operations and provide readiness for a national scale deployment. The focus of the project was (1) the improvement, refinement, and deployment of technology for the detection of cyber-attacks on utility operational technology (OT) and information technology (IT) networks and assets, including Supervisory Control and Data Acquisition Systems (SCADA) systems; and (2) support for containment and remediation of adversarial threats and actions against those systems and environments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Initial Inventory of Non-Technical Challenges to CCUS Deployment

The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARBUSA) project supports the U.S. Department of Energy (DOE) Office of Fossil Energy's (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made by the current Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The primary project objective is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) technologies. The Research Partners and a selected industry network of experienced CCUS project developers and operators will coordinate their capabilities to accelerate CCUS deployment by achieving four primary research objectives: 1) address key technical challenges; 2) facilitate data collection, sharing and analysis; 3) assess transportation and distribution infrastructure; and 4) promote regional technology transfer and dissemination of knowledge. The SECARB-USA Region includes the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia. Under subtask 5.2: Non-Technical Challenges to CCUS Deployment, the Southern States Energy Board (SSEB) will define and identify An Inventory of Non-Technical Challenges to CCUS Deployment. As an initial step, SSEB organized an Industry and Non-Governmental Organization (NGO) Working Group comprised of knowledgeable market participants to assist in the development of an initial list of non-technical challenges to CCUS development.

42 ENGINEERING↗
DOE OSTI2021

Baylor University Campus-Wide Deep Dive

In January 2020, staff members from the Engagement and Performance Operations Center (EPOC) and the Lonestar Education And Research Network (LEARN) met with researchers and staff at Baylor University for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support. Profiled scientific use cases included: - Experimental High Energy Physics (HEP) - Proton Computed Tomography (pCT) - Nutrition and Relation to Digestive Microbiome - Baylor University Core Research Facilities - Molecular Quantum-dot Cellular Automata (QCA), and Material Science of Quantum Computing - Modeling and Simulation of Low-Dimensional and Nano-Structured Materials - Computational Fluid Dynamics Material for this event included the written documentation from each of the research areas at Baylor University, documentation about the current state of technology support, and a write-up of the discussion that took place in person. The Case Studies highlighted the ongoing challenges that Baylor University has in supporting a cross-section of established and emerging research use cases. Each Case Study mentioned unique challenges which were summarized into common needs. These included: - Tradeoffs for network/software security, and usability of the resulting infrastructure. Better communication to set expectations and understand realities is required. - Computation use on campus is widespread and healthy. While no major problems were uncovered, upgrades to maintain current usage patterns and encourage growth will be required. - Storage is a critical need for enterprise use cases and research. In particular, a campus wide ‘storage architecture’ to support research use cases (e.g. instruments, data sharing) is required in the 2-5 year time window. - Instrumentation on campus is healthy and expanding. Technology must scale with this in the form of computation and storage. - Working with LEARN to upgrade network capacity (in multiples of 10G, or upgrades to 100G) will be required in the 1-3 year time frame. - Network monitoring and visibility will help to establish external science use cases. - Data sharing via portal systems is not currently a critical need, but growing in scope. EPOC can assist Baylor with options.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

V-INT: Automated Vulnerability Intelligence and Risk Assessment

The project team, including the University of Arkansas (UA) as the lead, the University of Arkansas at Little Rock (UALR), Network Perception (NP), and Bastazo, has successfully researched, developed, and demonstrated the V-INT toolset, and also integrated it into the commercial products of NP (i.e., NP-View) and Bastazo (i.e., Spartan). The end product is a cybersecurity software tool for energy utilities that can automatically assess the risks of software vulnerabilities in an organization’s assets considering the organization’s firewall policies. It allows security operators to identify the small portion of vulnerabilities that poses true threats to their system (i.e., those that are not protected by firewall policies) and prioritize the mitigation of these vulnerabilities to minimize risks. It also allows security operators to identify the vulnerability-induced attack paths under their organization’s firewall policy, providing effective decision supports for mitigating potential attacks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗
DOE OSTI2024

The Future of Vehicle Grid Integration: Harnessing the Flexibility of EV Charging

This document lays out a shared vision for a beneficial, EV-integrated future where EVs are safely and securely connected, reliably served, and harmonized with the electric grid. It was developed as part of the U.S. Department of Energy’s (DOE) EVGrid Assist initiative. Stakeholder input was gathered through individual and collective conversations, including eight listening sessions with more than 100 participants representing utilities of different sizes and operating structures, manufacturers of vehicles and chargers, national associations, standards organizations, Tribes, fleet managers, consumer advocates, charging network operators, community-based organizations, utility regulators, consultants, vendors, labor, and environmental justice organizations. This document focuses on the future of electric on-road U.S. transportation, specifically the integration of light-duty vehicles (LDV) and medium- and heavy-duty vehicles (MHDV) and their charging infrastructure with the electric grid. However, many of the insights here may apply to electrifying other transportation modes, as well as other distributed energy resources (DER).

EVGrid Assist initiative, EV-integrated future, el↗
DOE OSTI2024

The Future of Vehicle Grid Integration: Harnessing the Flexibility of EV Charging

This document lays out a shared vision for a beneficial, EV-integrated future where EVs are safely and securely connected, reliably served, and harmonized with the electric grid. It was developed as part of the U.S. Department of Energy’s (DOE) EVGrid Assist initiative. Stakeholder input was gathered through individual and collective conversations, including eight listening sessions with more than 100 participants representing utilities of different sizes and operating structures, manufacturers of vehicles and chargers, national associations, standards organizations, Tribes, fleet managers, consumer advocates, charging network operators, community-based organizations, utility regulators, consultants, vendors, labor, and environmental justice organizations. This document focuses on the future of electric on-road U.S. transportation, specifically the integration of light-duty vehicles (LDV) and medium- and heavy-duty vehicles (MHDV) and their charging infrastructure with the electric grid. However, many of the insights here may apply to electrifying other transportation modes, as well as other distributed energy resources (DER).

EVGrid Assist initiative, EV-integrated future, el↗
NASA NTRS2007

Solutions Network Formulation Report. The Potential Contribution of the Ocean Surface Topography Mission to the General NOAA Oil Monitoring Environment

Data collected by the OSTM could be used to provide a solution for the GNOME DST. GNOME, developed by NOAA?s Office of Response and Restoration Hazardous Materials Response Division, geospatially models oil spill trajectories using wind, current, river flow, and tidal data. Data collected by the OSTM would supply information about ocean currents and wind speeds. This Candidate Solution is in alignment with the Coastal Management, Water Management, Disaster Management, Public Health, Ecological Forecasting, and Homeland Security National Applications and will benefit society by improving the capabilities of emergency responders who evaluate an oil spill?s probable threat.

Hilbert, Kent↗