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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 OSTI2026

Integrating DOE ASCR Computing into HEPCloud through GlideinWMS

Fermilab's HEPCloud facility expands the laboratory's computing capacity by provisioning resources beyond the local grid, using GlideinWMS to deliver pilots to where experiments such as CMS and DUNE run. The High-Performance Computing (HPC) facilities of the DOE Office of Advanced Scientific Computing Research (ASCR) are a growing part of that pool. HEPCloud currently provisions NERSC over SSH, but NERSC is moving away from that path as it adopts multi-factor authentication and directs automated access to its Superfacility API and the DOE Integrated Research Infrastructure (IRI) APIs. Maintaining and extending access across the ASCR ecosystem now requires provisioning through these interfaces. This work adds new pilot submission paths to GlideinWMS for the NERSC Superfacility API, IRI, and Globus Compute. Each uses the provisioning model GlideinWMS already applies to batch resources, so experiments can run on ASCR computing resources without changes to their existing workflows. This work finally presents a comparison of the paths to guide which interfaces are best suited for different workflows.

Majumder, Meghanto [U. Houston (main)]↗
DOE OSTI2014

Physical unclonable functions: A primer

Physical unclonable functions (PUFs) make use of the measurable intrinsic randomness of physical systems to establish signatures for those systems. Thus, PUFs provide a means to generate unique keys that don't need to be stored in nonvolatile memory, and they offer exciting opportunities for new authentication and supply chain security technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Watchmen v3.1.0 Release Notes

This document describes the changes to Watchmen. This includes improvements to stability, search features, display of more detailed sample information and user access via authentication.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

CyPhyTown

A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.

Source record↗
DOE OSTI2014

CyPhyTown

A series of software programs that enables students to progress from completely unsecured control of devices to control that protects network commands with authentication, integrity and confidentiality. The working example provided is for turning LED lights on and off on a Raspberry Pi computer.

Source record↗
DOE OSTI2013

Hardware device to physical structure binding and authentication

Detection and deterrence of device tampering and subversion may be achieved by including a cryptographic fingerprint unit within a hardware device for authenticating a binding of the hardware device and a physical structure. The cryptographic fingerprint unit includes an internal physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generate an internal PUF value. Binding logic is coupled to receive the internal PUF value, as well as an external PUF value associated with the physical structure, and generates a binding PUF value, which represents the binding of the hardware device and the physical structure. The cryptographic fingerprint unit also includes a cryptographic unit that uses the binding PUF value to allow a challenger to authenticate the binding.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Quantum key distribution using card, base station and trusted authority

Techniques and tools for quantum key distribution ("QKD") between a quantum communication ("QC") card, base station and trusted authority are described herein. In example implementations, a QC card contains a miniaturized QC transmitter and couples with a base station. The base station provides a network connection with the trusted authority and can also provide electric power to the QC card. When coupled to the base station, after authentication by the trusted authority, the QC card acquires keys through QKD with a trusted authority. The keys can be used to set up secure communication, for authentication, for access control, or for other purposes. The QC card can be implemented as part of a smart phone or other mobile computing device, or the QC card can be used as a fillgun for distribution of the keys.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Quantum key distribution using card, base station and trusted authority

Techniques and tools for quantum key distribution ("QKD") between a quantum communication ("QC") card, base station and trusted authority are described herein. In example implementations, a QC card contains a miniaturized QC transmitter and couples with a base station. The base station provides a network connection with the trusted authority and can also provide electric power to the QC card. When coupled to the base station, after authentication by the trusted authority, the QC card acquires keys through QKD with a trust authority. The keys can be used to set up secure communication, for authentication, for access control, or for other purposes. The QC card can be implemented as part of a smart phone or other mobile computing device, or the QC card can be used as a fillgun for distribution of the keys.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗
DOE OSTI2026

Expandable Log Analyzing Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, IL]↗
DOE OSTI2014

Multi-factor authentication

Detection and deterrence of spoofing of user authentication may be achieved by including a cryptographic fingerprint unit within a hardware device for authenticating a user of the hardware device. The cryptographic fingerprint unit includes an internal physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generates a PUF value. Combining logic is coupled to receive the PUF value, combines the PUF value with one or more other authentication factors to generate a multi-factor authentication value. A key generator is coupled to generate a private key and a public key based on the multi-factor authentication value while a decryptor is coupled to receive an authentication challenge posed to the hardware device and encrypted with the public key and coupled to output a response to the authentication challenge decrypted with the private key.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Database-Agnostic Log Analysis and Monitoring Framework

Prior to my internship, I was informed that a previous intern had built a tool to analyse MongoDB logs and look for invalid access attempts, which served as a great reference point for my project. I was initially tasked with expanding on her prototype and filling in the gaps such as integrating it with the main monitoring tool the lab uses. Eventually, the scope grew, expanding to support other databases and a growing collection of tools. I organized the framework around an observer pattern, meaning one point in the program sending updates to the rest of the framework. Every time a log was read and parsed, it was sent to be processed by the tools, using the type of event as a means to determine which tools should get a chance to act on the log. This decouples the tools from the log reader, making future updates and additions much easier. The framework processes MongoDB logs at ~135,000 entries per second and PostgreSQL logs at ~170,500 entries per second, accurately detecting anomalies such as slow queries and connections from unknown addresses. This framework serves to fill gaps in database monitoring tools currently implemented at the lab, such as tracking failed authentication for PostgreSQL and MongoDB which had very minimal or none before this framework. National labs such as Fermilab hold sensitive data and valuable computing resources, making them attractive targets. Monitoring intrusion attempts on databases is made much easier by this comprehensive monitoring suite.

Clark, Dylan [Unlisted, US, IL; Fermilab]↗
DOE OSTI2020

Multi-View Convolutional Neural Network for Data Spoofing Cyber-Attack Detection in Distribution Synchrophasors

Security of Distribution Synchrophasors Data (DSD) is of paramount importance as the data is used for critical smart grid applications including situational awareness, advanced protection, and dynamic control. Unfortunately, the DSD are attractive targets for malicious attackers aiming to damage grid. Data spoofing is a new class of deceiving attack, where the DSD of one Phasor Measurement Units (PMUs) is tampered by other PMUs thereby spoiling measurement based applications. In order to address this issue, a source authentication based data spoofing attack detection method is proposed using Multi-view Convolutional Neural Network (MCNN). First, common components embedded in raw frequency measurements from DSD are removed by Savitzky-Golay (SG) filter. Second, fast S transform (FST) is utilized to extract representative spatial fingerprints via time frequency analysis. Third, the spatial fingerprint is fed to MCNN, which combines dilated and standard convolutions for automatic feather extraction and source identification. Finally, according to the output of MCNN, spoofing attack detection is performed via threshold criterion. Extensive experiments with actual DSD from multiple locations in FNET/Grideye are conducted to verify the effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Weighted Watson-Crick automata

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Perturbation-Based Diagnosis of False Data Injection Attack Using Distributed Energy Resources

Modern smart grid relies on various sensor measurements for its operational control. In a successful false data injection attack, the attacker manipulates the measurements from the grid sensors such that undetected errors are introduced into the estimates of the system parameters leading to catastrophic situations. This paper proposes a novel perturbation based false data injection attack detection mechanism that utilizes inverter based distributed energy resources (DERs) to create low magnitude perturbation signal in the distribution system voltage that is inconsequential to the normal grid operation. Two voltage sensitivity analysis based algorithms are designed to identify the optimal set of DERs that can create the voltage perturbation signal of desired magnitude. An analytical method of voltage sensitivity analysis is used to compute the magnitude of voltage perturbation signal at each node in a computationally efficient manner. Then, a detection mechanism is developed that checks for the presence of the perturbation sequence in each sensor measurement. A sensor measurement is deemed authentic if the voltage perturbation signal is present in the data. In case of sensor malfunction or cyber-attack, the perturbation signal will not be present in the measurement data. Performance of the proposed attack detection mechanism is validated via simulation of the IEEE 69 bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Deployable sensor system using mesh networking and satellite communication

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Bridge Kernel

The Bridge Kernel is a Jupyter Kernel for connecting to compute backends that implement the bridge kernel (bk) protocol. The bk protocol is a client-server protocol that emphasizes minimal dependencies, easy embedding with MPI, secure connections + authentication, and non-local backends with automatic tunneling.

Stitt, Thomas↗
DOE OSTI2017

Secure ICCP Final Report

Inter-Control Center Communications Protocol (ICCP), defined by the IEC 60870-6 TASE.2 standard, was developed to enable data exchange over wide area networks between electric system entities, including utility control centers, Independent System Operators (ISOs), Regional Transmission Operators (RTOs) and Independent Power Producers (IPP) also known as Non-Utility Generators (NUG). ICCP is an unprotected protocol, and as a result is vulnerable to such actions as integrity violation, interception or alteration, spoofing, and eavesdropping. Because of these vulnerabilities with unprotected ICCP communication, security enhancements, referred to as Secure ICCP, have been added and are included in the ICCP products that utilities have received since 2003 when the standard was defined. This has resulted in an ICCP product whose communication can be encrypted and authenticated to address these vulnerabilities.

97 MATHEMATICS AND COMPUTING↗