Designing a Secure Conveyance: Cyber-Physical Security Risk Mitigation Leveraging In-Vehicle Computers
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Hollifield, Sam [ORNL] (ORCID:0000000151499268)↗
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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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Cyber Infrastructure for the Smart Electric Grid
As electric power systems undergo a transformative upgrade with the integration of advanced technologies to enable the smarter electric grid, professionals who work in the area require a new understanding of the evolving complexity of the grid. Cyber Infrastructure for the Smart Electric Grid delivers a comprehensive overview of the fundamental principles of smart grid operation and control, smart grid technologies, including sensors, communication networks, computation, data management, and cyber security, and the interdependencies between the component technologies on which a smart grid's security depends. The book offers readers the opportunity to critically analyze the smart grid infrastructure needed to sense, communicate, compute, and control in a secure way.
communication networks↗
Final Technical Report
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97 MATHEMATICS AND COMPUTING↗
Verifying the Computational Integrity of Power Grid Controls with Zero-Knowledge Proof
The control of future power grids is migrating from a centralized to a distributed/decentralized scheme to enable a massive penetration of distributed energy resources with rising dependence on communication infrastructure. A common assumption made for most existing distributed/decentralized controllers is that local controllers would faithfully follow the designated controller dynamics based on the data received from communication channels. However, with increased probability of cyberattacks on Operational Technology infrastructure, such an assumption could be risky because proper execution of the controller dynamics is then built on trust in secure communication and computation. In this work, we leverage a cryptography technology known as zero-knowledge scalable transparent arguments of knowledge (zk-STARK) to verify the computational integrity of power grid control algorithms, with projected linear dynamics-based control schemes as the initial proof-of-concept test case. The method presented here converts the cybersecurity challenge of data integrity for grid control into a subset of computational integrity.
computational integrity↗
A Typology of Quantum-Classical Faults
This paper introduces an extended taxonomy of faults specific to hybrid quantum-classical systems, addressing the unique challenges that arise from integrating quantum accelerators into high-performance computing (HPC) infrastructures. Building on the foundational fault classification by Avizienis et al., we incorporate fault types unique to quantum computing-such as qubit decoherence, spontaneous gate errors, and photon loss-alongside traditional and human-induced faults including development errors, operational mistakes, and malicious attacks. Our taxonomy classifies faults by their origin (natural vs. human-made), intent (accidental, deliberate non-malicious, or malicious), system boundaries (internal vs. external), and persistence (transient to permanent). We also explore how different architectural integration patterns-ranging from tight coupling to loose on-premise and cloud-based configurations-shape the manifestation and propagation of faults. These scenarios are analyzed in terms of timing mismatches, interface inconsistencies, and security threats such as data tampering and denial-of-service attacks. Through this fault-centric lens, we aim to support the co-design of dependable quantum-classical systems and highlight the critical role that integration strategies play in ensuring reproducibility, resilience, and security across hybrid computing platforms.
Giusto, Edorado [University of Naples Federico II,↗
Computational Physics Overview [Slides]
Computational physics is an important part of the overall investment in National Security Science at LANL. Computational physics is the study and implementation of numerical analysis to solve problems in physics for which a quantitative theory already exists. Historically, computational physics was the first application of modern computers in science. There are three key elements to computational physics: mathematical models of physical phenomena and conservation equations, computer codes that implement these models, and computer platforms that execute the code instructions and manipulate the data.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
3 He Separation from US Liquid Natural Gas-Derived 4 He (Final Report)
This final report summarizes the technical and economic feasibility study conducted by Interlune, Lisbon Group, and Pacific Northwest National Laboratory on separating 3 He from 4 He derived from liquid natural gas (LNG) using magnetocaloric liquefaction (MCL), superleak heat-flush, and fractional distillation techniques. The project aims to address the growing shortage of 3 He, a critical resource for quantum computing and national security, by exploring a new domestic source, the bulk helium supply.
07 ISOTOPE AND RADIATION SOURCES↗
Access control and privacy in large distributed systems
Large scale distributed systems consists of workstations, mainframe computers, supercomputers and other types of servers, all connected by a computer network. These systems are being used in a variety of applications including the support of collaborative scientific research. In such an environment, issues of access control and privacy arise. Access control is required for several reasons, including the protection of sensitive resources and cost control. Privacy is also required for similar reasons, including the protection of a researcher's proprietary results. A possible architecture for integrating available computer and communications security technologies into a system that meet these requirements is described. This architecture is meant as a starting point for discussion, rather that the final answer.
Leiner, B. M.↗
Access control and privacy in large distributed systems
Large scale distributed systems consists of workstations, mainframe computers, supercomputers and other types of servers, all connected by a computer network. These systems are being used in a variety of applications including the support of collaborative scientific research. In such an environment, issues of access control and privacy arise. Access control is required for several reasons, including the protection of sensitive resources and cost control. Privacy is also required for similar reasons, including the protection of a researcher's proprietary results. A possible architecture for integrating available computer and communications security technologies into a system that meet these requirements is described. This architecture is meant as a starting point for discussion, rather that the final answer.
Leiner, B. M.↗
System Engineering on the Use for Ares I,V - the Simpler, the Better
The Ares I and Ares V Vehicles will utilize the J-2X rocket engine developed for NASA by the Pratt & Whitney Rocketdyne Company. The J-2X is an improved higher power version of the original J-2 engine used during the Apollo program. With higher power and updated requirements for safety and performance, the J-2X becomes a new engine using state-of-the-art design methodology, materials and manufacturing processes. The implementation of Systems Engineering (SE) principles enables the rapid J-2X development program to remain aligned with the ARES I and V vehicle programs, Meeting the aggressive development schedule is a challenge. Coordinating the best expertise thai NASA and PWR have to offer requires effectively utilizing resources at multiple sites. This presents formidable communication challenges. SE allows honest and open discussions of issues and problems. This simple idea is often overlooked in large and complex SE programs. Regular and effective meetings linking SE objectives to component designs are used to voice differences of opinions with customer and contractor in attendance so that the best mutual decisions can be made on the shortest possible schedule. Regular technical interchange meetings on secure program wide computer networks and CM processes are effective,in the "Controlled Change" process that exemplifies good SE. Good communication is a key effective SE implementation. The System of Systems approach is the vision of the Orion program which facilitates the establishment of dynamic SE processes at all levels including the engine. SE enables requirements evolution by facilitating organizational and process agility. Flow down and distribution of requirements is controlled by Allocation Reports which breakdown numerical design objectives (weight, reliability, etc.) into quanta goals for each component area. Linked databases of design and verification requirements helps eliminate redundancy and potential mistakes inherent m separated systems. Another tool, the Architecture Design Description, is being used to control J-2X system architecture and effectively communicate configuration changes to those involved in the design process. But the proof is in successful program accomplishment. The SE is the methodology being used to meet the challenge of completing J-2X engine certification 2 years ahead of any engine program ever developed at PWR. The Ares I SE system of systems has delivered according to expectations thus far. All major design reviews (SRR. PDR, CDR) have been successfully conducted to satisfy overall program objectives using SE as the basis for accomplishment. The paper describes SE tools and techniques utilized to achieve this success.
Kelly, William↗
Risk Assessment Overview
Risk assessment is used in many industries to identify and manage risks. Initially developed for use on aeronautical and nuclear systems, risk assessment has been applied to transportation, chemical, computer, financial, and security systems among others. It is used to gain an understanding of the weaknesses or vulnerabilities in a system so modification can be made to increase operability, efficiency, and safety and to reduce failure and down-time. Risk assessment results are primary inputs to risk-informed decision making; where risk information including uncertainty is used along with other pertinent information to assist management in the decision-making process. Therefore, to be useful, a risk assessment must be directed at specific objectives. As the world embraces the globalization of trade and manufacturing, understanding the associated risk become important to decision making. Applying risk assessment techniques to a global system of development, manufacturing, and transportation can provide insight into how the system can fail, the likelihood of system failure and the consequences of system failure. The risk assessment can identify those elements that contribute most to risk and identify measures to prevent and mitigate failures, disruptions, and damaging outcomes. In addition, risk associated with public and environment impact can be identified. The risk insights gained can be applied to making decisions concerning suitable development and manufacturing locations, supply chains, and transportation strategies. While risk assessment has been mostly applied to mechanical and electrical systems, the concepts and techniques can be applied across other systems and activities. This paper provides a basic overview of the development of a risk assessment.
Prassinos, Peter G.↗
Revealing conductivity of p-type delta layer systems for novel computing applications
This project uses a quantum simulation technique to reveal the true conducting properties of novel atomic precision advanced manufacturing materials. With Moore's law approaching the limit of scaling for the CMOS technology, it is crucial to provide the best computing power and resources to National Security missions. Atomic precision advanced manufacturing-based computing systems can become the key to the design, use, and security of modern weapon systems, critical infrastructure, and communications. We will utilize the state-of-the-art computational methodology to create a predictive simulator for p-type atomic precision advanced manufacturing systems, which may also find applications in counterfeit detection and anti-tamper.
97 MATHEMATICS AND COMPUTING↗
Machine Learning-based Intrusion Detection for Smart Grid Computing: A Survey
Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.
SCADA↗
Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources
Applications which fuse machine learning and simulation are rarely best served by a single computing resource. Highly parallel simulation codes are best deployed on super- computers, while AI tasks used to decide which simulations to perform may be best suited to specialized accelerators. Here we present a Function-as-a-Service (FaaS) system for executing complex, distributed computational campaigns that achieves performance parity with conventional workflow systems without the complexities of secure network connections between compute providers. One innovation enabling high performance is a subsystem that directly moves task data between sites, separate from the cloud-hosted FaaS system used to distribute task instructions. We also introduce a flexible scheduling system that allows us access factor of 2 trade offs between the amount of resources required to solve a problem at each compute site. We anticipate that this system will upgrade multi-site applications from demonstration projects to routine practice in computational science.
Ward, Logan↗
A Domain-Decomposed Multi-Level Method for Adaptively Refined Cartesian Grids with Embedded Boundaries
The work presents a new method for on-the-fly domain decomposition technique for mapping grids and solution algorithms to parallel machines, and is applicable to both shared-memory and message-passing architectures. It will be demonstrated on the Cray T3E, HP Exemplar, and SGI Origin 2000. Computing time has been secured on all these platforms. The decomposition technique is an outgrowth of techniques used in computational physics for simulations of N-body problems and the event horizons of black holes, and has not been previously used by the CFD community. Since the technique offers on-the-fly partitioning, it offers a substantial increase in flexibility for computing in heterogeneous environments, where the number of available processors may not be known at the time of job submission. In addition, since it is dynamic it permits the job to be repartitioned without global communication in cases where additional processors become available after the simulation has begun, or in cases where dynamic mesh adaptation changes the mesh size during the course of a simulation. The platform for this partitioning strategy is a completely new Cartesian Euler solver tarcreted at parallel machines which may be used in conjunction with Ames' "Cart3D" arbitrary geometry simulation package.
Aftosmis, M. J.↗
Secure Large-Scale Airport Simulations Using Distributed Computational Resources
To fully conduct research that will support the far-term concepts, technologies and methods required to improve the safety of Air Transportation a simulation environment of the requisite degree of fidelity must first be in place. The Virtual National Airspace Simulation (VNAS) will provide the underlying infrastructure necessary for such a simulation system. Aerospace-specific knowledge management services such as intelligent data-integration middleware will support the management of information associated with this complex and critically important operational environment. This simulation environment, in conjunction with a distributed network of supercomputers, and high-speed network connections to aircraft, and to Federal Aviation Administration (FAA), airline and other data-sources will provide the capability to continuously monitor and measure operational performance against expected performance. The VNAS will also provide the tools to use this performance baseline to obtain a perspective of what is happening today and of the potential impact of proposed changes before they are introduced into the system.
McDermott, William J.↗
Secure Federated Learning Across Heterogeneous Cloud and High-Performance Computing Resources: A Case Study on Federated Fine-Tuning of LLaMA 2
Federated learning enables multiple data owners to collaboratively train robust machine learning models without transferring large or sensitive local datasets by only sharing the parameters of the locally trained models. Here, in this article, we elaborate on the design of our Advanced Privacy-Preserving Federated Learning (APPFL) framework, which streamlines end-to-end secure and reliable federated learning experiments across cloud computing facilities and high-performance computing resources by leveraging Globus Compute, a distributed function as a service platform, and Amazon Web Services. We further demonstrate the use case of APPFL in fine-tuning an LLaMA 2 7B model using several cloud resources and supercomputers.
97 MATHEMATICS AND COMPUTING↗
A survey of software implementations used by application codes in the Exascale Computing Project
The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.
97 MATHEMATICS AND COMPUTING↗