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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Secure Collaborative Environment for Seamless Sharing of Scientific Knowledge

In a secure collaborative environment, tera-bytes of data generated from powerful scientific instruments are used to train secure machine learning (ML) models on exascale computing systems, which are then securely shared with internal or external collaborators as cloud-based services. Devising such a secure platform is necessary for seamless scientific knowledge sharing without compromising individual, or institute-level, intellectual property and privacy details. By enabling new computing opportunities with sensitive data, we envision a secure collaborative environment that will play a significant role in accelerating scientific discovery. Several recent technological advancements have made it possible to realize these capabilities. In this paper, we present our efforts at ORNL toward developing a secure computation platform. We present a use case where scientific data generated from complex instruments, like those at the Spallation Neutron Source (SNS), are used to train a differential privacy enabled deep learning (DL) network on Summit, which is then hosted as a secure multi-party computation (MPC) service on ORNL’s Compute and Data Environment for Science (CADES) cloud computing platform for third-party inference. In this feasibility study, we discuss the challenges involved, elaborate on leveraged technologies, analyze relevant performance results and present the future vision of our work to establish secure collaboration capabilities within and outside of ORNL.

Yoginath, Srikanth↗
DOE OSTI2016

Knowledge management: Role of the the Radiation Safety Information Computational Center (RSICC)

The Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory (ORNL) is an information analysis center that collects, archives, evaluates, synthesizes and distributes information, data and codes that are used in various nuclear technology applications. RSICC retains more than 2,000 software packages that have been provided by code developers from various federal and international agencies. RSICC’s customers (scientists, engineers, and students from around the world) obtain access to such computing codes (source and/or executable versions) and processed nuclear data files to promote on-going research, to ensure nuclear and radiological safety, and to advance nuclear technology. The role of such information analysis centers is critical for supporting and sustaining nuclear education and training programs both domestically and internationally, as the majority of RSICC’s customers are students attending U.S. universities. Additionally, RSICC operates a secure CLOUD computing system to provide access to sensitive export-controlled modeling and simulation (M&S) tools that support both domestic and international activities. This presentation will provide a general review of RSICC’s activities, services, and systems that support knowledge management and education and training in the nuclear field.

Valentine, Timothy↗
DOE OSTI2025

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗
DOE OSTI2016

Multiple operating system rotation environment moving target defense

Systems and methods for providing a multiple operating system rotation environment ("MORE") moving target defense ("MTD") computing system are described. The MORE-MTD system provides enhanced computer system security through a rotation of multiple operating systems. The MORE-MTD system increases attacker uncertainty, increases the cost of attacking the system, reduces the likelihood of an attacker locating a vulnerability, and reduces the exposure time of any located vulnerability. The MORE-MTD environment is effectuated by rotation of the operating systems at a given interval. The rotating operating systems create a consistently changing attack surface for remote attackers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Energy Supply Security Index (eesi) v0.1.0

This software computes different metrics that quantify energy supply security. It computes metrics for the amount of energy self-production, autonomy, system adequacy, self-sufficiency and autarky. The software has been developed to compute metrics that are introduced in a journal manuscript, and the software is intended to be published to make the underlying metric calculation accessible and reproducible to the reader of the article. Potential use of the software is for policymakers, energy planners and researchers to guide energy system infrastructure decisions.

Sulzer, Matthias [Swiss Federal Laboratories for M↗
DOE OSTI2020

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Secure Power Systems Professional Phase III Final Report: Recruiting, Selecting and Developing Secure Power Systems Professionals

With significant numbers of power system experts retiring and a continuing trend of increasing complexity in modern power systems, there is a need throughout the power industry for cybersecurity awareness and competence in tasks that previously had no cyber components. To address these challenges, the U.S. Department of Energy established the Secure Power Systems Professional (SPSP) project to develop resources for job definition and competency analysis along with tools to guide assessment and curriculum design and to help identify and develop required knowledge, skills, and abilities in technical and operational power systems cybersecurity. The major accomplishments in Phase III of the project, which were built upon foundations laid in the first two phases, were (a) development and fielding of a Recruitment Guide for Human Resources and Hiring Managers and a Guide to Developing SPSPs; (b) development of psychometrically validated job profiles for identified SPSP job roles; (c) development of behavioral interview guidelines that list competencies necessary to perform each job role; and (d) development of guidelines that aid in evaluating individual and team performance and that inform strategic planning for organizations in selection, development and retention of SPSP professionals. The outcomes of the project can be immediately applied by human resources professionals, recruiters and hiring managers to assist in the recruitment, selection, and training of SPSPs, as well as to identify needed skills to grow existing employees into SPSPs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

High-Q cavity interface for color centers in thin film diamond

Quantum information technology offers the potential to realize unprecedented computational resources via secure channels distributing entanglement between quantum computers. Diamond, as a host to optically-accessible spin qubits, is a leading platform to realize quantum memory nodes needed to extend such quantum links. Photonic crystal (PhC) cavities enhance light-matter interaction and are essential for an efficient interface between spins and photons that are used to store and communicate quantum information respectively. Here, we demonstrate one- and two-dimensional PhC cavities fabricated in thin-film diamonds, featuring quality factors (Q) of 1.8 × 10 5 and 1.6 × 10 5 , respectively, the highest Qs for visible PhC cavities realized in any material. Importantly, our fabrication process is simple and high-yield, based on conventional planar fabrication techniques, in contrast to the previous with complex undercut processes. We also demonstrate fiber-coupled 1D PhC cavities with high photon extraction efficiency, and optical coupling between a single SiV center and such a cavity at 4 K achieving a Purcell factor of 18. The demonstrated photonic platform may fundamentally improve the performance and scalability of quantum nodes and expedite the development of related technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Quantum Realism

In this issue, we review quantum computing: what has been accomplished and what is its future. We introduce a collection of opinions about the realistic challenges facing the future of quantum computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Virtual Power Plants: Pilots, Challenges, and Innovations Shaping Future Development

Virtual Power Plants (VPPs) aggregate distributed energy resources (DERs) to provide grid services traditionally delivered by centralized power plants. This article reviews the current state of VPP deployment, highlighting business models, compensation mechanisms, and global pilot projects. While VPPs offer benefits such as grid flexibility, resilience, and cost savings, challenges remain in communication infrastructure, regulatory frameworks, market access, and customer engagement. To address these, we propose a scalable, privacy-preserving hierarchical VPP architecture that coordinates with distribution utilities and preserves customer data. We also present the Integrated T&D Control Room of the Future as a key test bed for validating and accelerating VPP adoption. These innovations can help transition VPPs from pilot programs to integral components of a modern, reliable power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

IEEE TRANSACTIONS ON CYBERNETICS

MODERN societies depend on complex and critical infrastructures for energy, transportation, sustenance, medical care, emergency response, communications security. As computers, automation, and information technology (IT) have advanced, these technologies have been exploited to enhance the efficiency of operating the processes that make up these infrastructures

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Beyond the Hype: An Evaluation of Commercially Available Machine-Learning-Based Malware Detectors

There is a lack of scientific testing of commercially available malware detectors, especially those that boast accurate classification of never-before-seen (i.e., zero-day) files using machine learning (ML). Consequently, efficacy of malware detectors is opaque, inhibiting end users from making informed decisions and researchers from targeting gaps in current detectors. In this paper, we present a scientific evaluation of four prominent commercial malware detection tools to assist an organization with two primary questions: To what extent do ML-based tools accurately classify previously and never-before-seen files? Is purchasing a network-level malware detector worth the cost? To investigate, we tested each tool against 3,536 total files (2,554 or 72% malicious, 982 or 28% benign) of a variety of file types, including hundreds of malicious zero-days, polyglots, and APT-style files, delivered on multiple protocols. We present statistical results on detection time and accuracy, consider complementary analysis (using multiple tools together), and provide two novel applications of the recent cost-benefit evaluation procedure of Iannacone & Bridges. Although the ML-based tools are more effective at detecting zero-day files and executables, the signature-based tool might still be an overall better option. Both network-based tools provide substantial (simulated) savings when paired with either host tool, yet both show poor detection rates on protocols other than HTTP or SMTP. Our results show that all four tools have near-perfect precision but alarmingly low recall, especially on file types other than executables and office files—37% of malware, including all polyglot files, were undetected. Priorities for researchers and takeaways for end users are given. Code for future use of the cost model is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Blockchain Based Remote Data Integrity Checking Tool v1.0

Computer System Security: The software is used to perform remote data integrity checking without relying on a single third party. In order to remove the trusted third party our tool uses distributed ledger (Blockchain) technology. The ledger is used to store evidences (in the form of hash values). These values are used as an input in the integrity checking process.

Wonjiga, Amir↗
DOE OSTI2016

High Brightness Room Temperature III-Nitride Based Single Photon Source

Single photon sources (SPS) are quantum light sources where photons are emitted one at a time instead of randomly (e.g. lasers) or in a bunch (e.g. thermal) that can significantly impact quantum information science (computing and secure communications) and quantum metrology. Some highly desirable features of SPS are low second order correlation (g 2 ),controllable emission, electrically injected room temperature operation with high photon rate, high extraction efficiency and controllable directionality. Approaches taken thus far using different material systems have only addressed a subset of these features. III-nitride based approach offers a clear pathway to deterministic, room temperature (R.T.), electrically injected practical SPS as one can potentially also leverage the knowledge and technology from the light emitting diode (LED) world. Here we will describe a hybrid approach wherein a TiO2 based photonic crystal (PC) cavity is fabricated around an InGaN quantum dot (QD) embedded nanoscale post deterministically placed inside a photonic crystal cavity. This project takes the initial steps necessary to achieve a practical, compact SPS. We have used finite difference time domain simulations to optimize the cavity design to achieve high quality factor, mode overlap with QD and high extraction. We have fabricated InGaN quantum dots using a top-down approach involving dry etch and photoelectrochemical etch followed by electron beam lithography based nanofabrication of photonic crystal cavities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Securing machine learning models

We discuss the challenges and approaches to securing numeric computation against adversaries who may want to discover hidden parameters or values used by the algorithm. We discuss techniques that are both cryptographic and non-cryptographic in nature. Cryptographic solutions are either not yet algorithmically feasible or currently require more computational resources than are reasonable to have in a deployed setting. Non-cryptographic solutions may be computationally faster, but these cannot stop a determined adversary. For one such non-cryptographic solution, mixed Boolean arithmetic, we suggest a number of improvements that may protect the obfuscated calculation against current automated deobfuscation methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Information-Theoretically Secure Distributed Machine Learning

A previously obscure area of cryptography known as Secure Multiparty Computation (MPC) is enjoying increased attention in the field of privacy-preserving machine learning (ML), because ML models implemented using MPC can be uniquely resistant to capture or reverse engineering by an adversary. In particular, an adversary who captures a share of a distributed MPC model provably cannot recover the model itself, nor data evaluated by the model, even by observing the model in operation. We report on our small project to survey current MPC software and judge its practicality for fielding mission-relevant distributed machine learning models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Technical Guide for Implementing Cybersecurity Continuous Monitoring in the Nuclear Industry

A technical guide to assist the nuclear industry in implementing cybersecurity continuous monitoring program. The guide walks through the steps to develop a cybersecurity continuous monitoring program and provides details relative to the nuclear industry. It also includes a series of examples of optional metrics to be used, and technologies that can be useful when implementing a continuous monitoring program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗