Search NASA⌕ Search

SEARCH · Search NASA

Results for “computer 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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Software For Monitoring A Computer Network

SNMAT is rule-based expert-system computer program designed to assist personnel in monitoring status of computer network and identifying defective computers, workstations, and other components of network. Also assists in training network operators. Network for SNMAT located at Space Flight Operations Center (SFOC) at NASA's Jet Propulsion Laboratory. Intended to serve as data-reduction system providing windows, menus, and graphs, enabling users to focus on relevant information. SNMAT expected to be adaptable to other computer networks; for example in management of repair, maintenance, and security, or in administration of planning systems, billing systems, or archives.

Lee, Young H.↗
NASA NTRS2008

PyPele Rewritten To Use MPI

A computer program known as PyPele, originally written as a Pythonlanguage extension module of a C++ language program, has been rewritten in pure Python language. The original version of PyPele dispatches and coordinates parallel-processing tasks on cluster computers and provides a conceptual framework for spacecraft-mission- design and -analysis software tools to run in an embarrassingly parallel mode. The original version of PyPele uses SSH (Secure Shell a set of standards and an associated network protocol for establishing a secure channel between a local and a remote computer) to coordinate parallel processing. Instead of SSH, the present Python version of PyPele uses Message Passing Interface (MPI) [an unofficial de-facto standard language-independent application programming interface for message- passing on a parallel computer] while keeping the same user interface. The use of MPI instead of SSH and the preservation of the original PyPele user interface make it possible for parallel application programs written previously for the original version of PyPele to run on MPI-based cluster computers. As a result, engineers using the previously written application programs can take advantage of embarrassing parallelism without need to rewrite those programs.

Hockney, George↗
DOE OSTI2022

Development of an end state vision to implement digital monitoring in nuclear plants

Transitioning from an onsite Maintenance & Diagnostics Center to cloud-based services offers many new opportunities with computing power and storage, but also new challenges in terms of networking and security. This report will cover everything required for that transition including data processing and uploading to cloud services, feature selection, model creation, and result visualization for decision making. Although there are several other cloud-based services (e.g. Amazon Web Services and Google Cloud), this report explores Microsoft Azure to simplify nomenclature and maintain a consistent focus. Many of the services offered by Microsoft Azure are also available in the other cloud-based services, and their differences have been recorded in other literature. The Azure services most important to a nuclear power plant including networking & security, storage & databases, and Artificial Intelligence (AI) are reviewed here. Networking covers all aspects related to communication to Azure resources including security, privacy, and redundancy. Storage & databases includes data storage, upgrading, patching, backups, and monitoring. The AI services allows the user access to the machine learning (ML) techniques developed with Azure including automated ML, anomaly detection, computer vision, and natural language processing. This report summaries the features, capabilities, and challenges when using cloud-based services in a user-friendly manner.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Secure Intra-Body Wireless Communications (SIWiC) System Project

SIWiC System is a project to investigate, design and implement future wireless networks of implantable sensors in the body. This futuristic project is designed to make use of the emerging and yet-to-emerge technologies, including ultra-wide band (UWB) for wireless communications, smart implantable sensors, ultra low power networking protocols, security and privacy for bandwidth and power deficient devices and quantum computing. Progress in each of these fronts is hindered by the needs of breakthrough. But, as we will see in this paper, these major challenges are being met or will be met in near future. SIWiC system is a network of in-situ wireless devices that are implanted to coordinate sensed data inside the body, such as symptoms monitoring collected internally, or biometric data collected of an outside object from within the intra-body network. One node has the capability of communicating outside the body to send data or alarm to a relevant authority, e.g., a remote physician.

Ahmad, Aftab↗
DOE OSTI2026

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The Impact of Time-Aware Design Choices in ICS Anomaly Detection

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and na¨ıve imputation— prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensordecomposition– based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Multifractal Characterization of Distribution Synchrophasors for Cybersecurity Defense of Smart Grids

“Source ID Mix” spoofing emerged as a new type of cyber-attack on Distribution Synchrophasors (DS) where adversaries have the capability to swap the source information of DS without changing the measurement values. Accurate detection of such a highly-deceptive attack is a challenging task especially when the spoofing attack happens on short fragments of DS recorded within a relatively small geographical scale. Herein this letter proposes an effective approach to detect this cyber-attack by realizing the multifractal characteristics of DS measurements. First, the multifractal cross-correlation of DS measured at multiple intra-state locations is revealed. Then the derived correlation is integrated with weighted two-dimensional multifractal surface interpolation to reconstruct quasi high-resolution signals. Finally, informative location-specific signatures are extracted from the high-resolution DS and they are integrated with advanced machine learning techniques for source authentication. Experiments using the real-life DS are performed to verify the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Design Choices in Anomaly Detection for Industrial Control Systems: Insights from Gas Pipeline Data

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and naïve imputation—prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensor-decomposition–based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

System security in the space flight operations center

The Space Flight Operations Center is a networked system of workstation-class computers that will provide ground support for NASA's next generation of deep-space missions. The author recounts the development of the SFOC system security policy and discusses the various management and technology issues involved. Particular attention is given to risk assessment, security plan development, security implications of design requirements, automatic safeguards, and procedural safeguards.

Wagner, David A.↗
DOE OSTI2022

Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic, native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered, or lightweight solutions adapted to ultra-reliable low-latency communications (URLLC) but whose security properties remain under discussion. Although different 5G network slices may have different requirements, in general, both visions seem to fall short at provisioning secure URLLC in the future. In this work we address this challenge, by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks. We categorize those new security components into different groups according to their purpose and deployment scope. We propose to analyze them in the context of existing 5G architectures using two different approaches. First, using model checking techniques, we will evaluate the probability of an attacker to be successful against each security solution. Second, using analytical models, we will analyze the impact of these security mechanisms in terms of delay, throughput consumption, and reliability. Finally, we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture. Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced, dedicated non-native mechanisms could only guarantee secure URLLC with a probability of ~55%.

5G networks↗
DOE OSTI2022

An Intelligent Distributed Ledger Construction Algorithm for IoT

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.

multi-arm bandit↗
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 OSTI2017

Cyber security using multi-threaded architecture data diode at the NBSR - 114

Ongoing upgrades for the control room of the National Bureau of Standards Reactor (NBSR) located at the National Institute of Standards and Technology (NIST) require the ability to collect sensor data from the secured reactor network and transfer to the outside network for trend analysis, while maintaining the security of the reactor network. To accomplish this, a data diode was created to provide a physical barrier that prevents any outside data from reaching the secured reactor network. The hardware of the data diode consists of two embedded computers, running Unix based operating systems, connected by three DB-9 serial cables. The serial cables have been modified so that only two wires, a ground and a transmission line, provide connection between the computers. The data diode relies on a multi-threaded architecture to collect and simultaneously transfer data over three serial connections. A software program, implemented in Java, has been written to request data from the digital recorders installed to monitor the NBSR process instrumentation and transfer that data across the serial connections. The data diode can collect over 1200 data points from multiple digital recorders each second. The collected data can then be stored in a relational database for later analysis. The source codes for the software are available open source on GitHub. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Real-World Cyber Security Demonstration for Networked Electric Drives

In this article, we present the design and implementation of a cyber-physical security testbed for networked electric drive systems, aimed at conducting real-world security demonstrations. To our knowledge, this is one of the first security testbeds for networked electric drives, seamlessly integrating the domains of power electronics and computer science, and cybersecurity. By doing so, the testbed offers a comprehensive platform to explore and understand the intricate and often complex interactions between cyber and physical systems. The core of our testbed consists of four electric machine drives, meticulously configured to emulate small-scale but realistic information technology (IT) and operational technology (OT) networks. This setup both provides a controlled environment for simulating a wide array of cyber-attacks, and mirrors potential real-world attack scenarios with a high degree of fidelity. The testbed serves as an invaluable resource for the study of cyber-physical security, offering a practical and dynamic platform for testing and validating cybersecurity measures in the context of networked electric drive systems. As a concrete example of the testbed's capabilities, we have developed and implemented a Python-based script designed to execute step-stone attacks over a wireless local area network (WLAN). This script leverages a sequence of target IP addresses, simulating a real-world attack vector that could be exploited by adversaries. To counteract such threats, we demonstrate the efficacy of our developed cyber-attack detection algorithms, which are integral to our testbed's security framework. Furthermore, the testbed incorporates a real-time visualization system using InfluxDB and Grafana, providing a dynamic and interactive representation of networked electric drives and their associated security monitoring mechanisms. This visualization component not only enhances the testbed's usability but also offers insightful, real-time data for researchers and practitioners, thereby facilitating a deeper understanding of cyber-physical security dynamics in networked electric drive systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

Genomics and Proteomics Based Security Protocols for Secure Network Architectures

A hardware design that integrates live and algorithmic inhabitants to produce patterns of gene expression in vivo and in silico Protocols and algorithms based upon the processes of regulation of gene expression to produce cryptographic representations of genes, RNA, proteins, and gene expression to perform authentication and confidentiality functions for computers and networks. A network concept of operations integrating all of the above into existing legacy networks.

Security Genomics↗
DOE OSTI2021

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.

25 ENERGY STORAGE↗