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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Privacy Preserving Federated Learning for Advanced Scientific Ecosystems

We present a framework to provide privacy preserving (PP) federating learning (FL) across multiple computational and experimental facilities. This work joins the compute capabilities of National Energy Research Scientific Computing Center (NERSC) and Oak Ridge National Laboratory Research Cloud (ORC) with simulated experimental data, such as those produced at the SLAC National Accelerator Laboratory and Spallation Neutron Source (SNS). We describe the software infrastructure developed to provide privacy for computational and experimental networks. We developed algorithmic privacy across the federated system by embedding database security, computation, and communication into the federation architecture, utilizing scientific tools developed by the experimental community.

Archibald, Rick [ORNL] (ORCID:0000000245389780)↗
DOE OSTI2022

Communication systems and methods

A communication system is provided that include one or more processors that are configured to instruct computing devices that communicate messages with each other via a time-sensitive network to securely exchange the messages using secret information, ad direct the computing devices to exchange the secret information via a dedicated quantum channel in the time-sensitive network. The one or more processors are also configured to determine a quantum channel synchronization time associated with the secret information exchanged via the dedicated quantum channel, and modify a local classical oscillator based on the quantum channel synchronization time, the local classical oscillator configured to provide a current time.

Bush, Stephen Francis↗
DOE OSTI2024

End-to-End Encryption for Cyber-Physical Systems Using Fully Homomorphic Encryption

Cyber-physical systems require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This presentation introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Encrypted Control Using Modified Learning With Errors-based Schemes

Cyber-physical systems (CPSs) require reliable, safe, and secure control of critical infrastructure, combining computational and networking capabilities, which heighten the risk of cyber attacks. These attacks can disrupt the physical process, causing unforeseen consequences. One solution is the use of fully homomorphic encryption (FHE) to protect the control loop, allowing for secure computations and communications without compromising signal and control system privacy. The challenge with FHE, however, is its requirement for inputs to be integers. This paper introduces a modified Learning With Errors (LWE) FHE approach that encodes control system dynamics and signals into integers. Our proposed scheme leverages a generalized LWE encoding function and modifies the Gentry-Sahai-Waters (GSW) gadget decomposition tool to encrypt the control system. Using the modified LWE scheme, we formalize a fully encrypted control system, supported by simulated results.

42 - ENGINEERING↗
DOE OSTI2016

Best Paper Award: Gathering Threat Intelligence Through Computer Network Deception

Presented at the 2016 IEEE International Symposium on Technologies for Homeland Security (HST), this LDRD-funded research received a Best Paper award, the highest award presented at the conference. The research focused on developing, implementing, and testing a novel computer network operations architecture that enables proactive defense by managing and monitoring enterprise resource allocations and network flows. The architecture leverages three emerging concepts: software-defined networks, cloud computing, and deception, to enable the detection and identification of anomalous access and intrusions to adjust to the dynamic nature of the adversary and to provide a mechanism to discover and react to the adversary’s attacks in a methodical and proactive manner. Additionally, the work allows network defenders to gather information on an adversary’s tools, tactics and procedures, providing insight into the “what, why, and how” of the adversary’s operations. A summary of the work presented at IEEE can be found at http://tiny.sandia.gov/8d8lu.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Mathematical approaches to secure in-vehicle networks

Modern vehicles rely on numerous small computers called electronic control units (ECUs) that continually communicate life-critical messages, e.g., wheel speeds and steering angle, through a few controller area networks (CANs). Originally designed as a closed network for the life of the vehicle, CAN protocol developed bereft of security features (e.g., authentication or encryption). For emission testing, updates, and other diagnostics, vehicle CANs are now physically accessible, but this comes with vulnerability to cyber attack. Mandatory on-board diagnostic ports (OBD-II) provide adversaries with direct access to the vehicle. Remote attacks, e.g., via Bluetooth or cellular connections, are possible but require deep expertise. In short, the critical networks for vehicle functionality are exposed to remote and local cyber attacks with little to no built-in defenses. Most notably, the infamous 2015 research of Miller and Valasek exhibited a remote takeover of a Jeep’s brakes resulting in a massive recall and ample media coverage.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Encryption for Remote Control via Internet or Intranet

A data-communication protocol has been devised to enable secure, reliable remote control of processes and equipment via a collision-based network, while using minimal bandwidth and computation. The network could be the Internet or an intranet. Control is made secure by use of both a password and a dynamic key, which is sent transparently to a remote user by the controlled computer (that is, the computer, located at the site of the equipment or process to be controlled, that exerts direct control over the process). The protocol functions in the presence of network latency, overcomes errors caused by missed dynamic keys, and defeats attempts by unauthorized remote users to gain control. The protocol is not suitable for real-time control, but is well suited for applications in which control latencies up to about 0.5 second are acceptable. The encryption scheme involves the use of both a dynamic and a private key, without any additional overhead that would degrade performance. The dynamic key is embedded in the equipment- or process-monitor data packets sent out by the controlled computer: in other words, the dynamic key is a subset of the data in each such data packet. The controlled computer maintains a history of the last 3 to 5 data packets for use in decrypting incoming control commands. In addition, the controlled computer records a private key (password) that is given to the remote computer. The encrypted incoming command is permuted by both the dynamic and private key. A person who records the command data in a given packet for hostile purposes cannot use that packet after the public key expires (typically within 3 seconds). Even a person in possession of an unauthorized copy of the command/remote-display software cannot use that software in the absence of the password. The use of a dynamic key embedded in the outgoing data makes the central-processing unit overhead very small. The use of a National Instruments DataSocket(TradeMark) (or equivalent) protocol or the User Datagram Protocol makes it possible to obtain reasonably short response times: Typical response times in event-driven control, using packets sized .300 bytes, are <0.2 second for commands issued from locations anywhere on Earth. The protocol requires that control commands represent absolute values of controlled parameters (e.g., a specified temperature), as distinguished from changes in values of controlled parameters (e.g., a specified increment of temperature). Each command is issued three or more times to ensure delivery in crowded networks. The use of absolute-value commands prevents additional (redundant) commands from causing trouble. Because a remote controlling computer receives "talkback" in the form of data packets from the controlled computer, typically within a time interval < or =1 s, the controlling computer can re-issue a command if network failure has occurred. The controlled computer, the process or equipment that it controls, and any human operator(s) at the site of the controlled equipment or process should be equipped with safety measures to prevent damage to equipment or injury to humans. These features could be a combination of software, external hardware, and intervention by the human operator(s). The protocol is not fail-safe, but by adopting these safety measures as part of the protocol, one makes the protocol a robust means of controlling remote processes and equipment by use of typical office computers via intranets and/or the Internet.

Lineberger, Lewis↗
DOE OSTI2017

Order priors for Bayesian network discovery with an application to malware phylogeny

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges) in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Using advanced data structures to enable responsive security monitoring

Write-optimized data structures (WODS), offer the potential to keep up with cyberstream event rates and give sub-second query response for key items like IP addresses. These data structures organize logs as the events are observed. To work in a real-world environment and not fill up the disk, WODS must efficiently expire older events. As the basis for our research into organizing security monitoring data, we implemented a tool, called Diventi, to index IP addresses in connection logs using RocksDB (a write-optimized LSM tree). In this work, we extended Diventi to automatically expire data as part of the data structures’ normal operations. We guarantee that Diventi always tracks the N most recent events and tracks no more than N + k events for a parameter k < N, while ensuring the index is opportunistically pruned. To test Diventi at scale in a controlled environment, we used anonymized traces of IP communications collected at SuperComputing 2019. We synthetically extended the 2.4 billion connection events to 100 billion events. We tested Diventi vs. Elasticsearch, a common log indexing tool. In our test environment, Elasticsearch saw an ingestion rate of at best 37,000 events/s while Diventi sustained ingestion rates greater than 171,000 events/s. Our query response times were as much as 100 times faster, typically answering queries in under 80 ms. Furthermore, we saw no noticeable degradation in Diventi from expiration. We have deployed Diventi for many months where it has performed well and supported new security analysis capabilities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

The Father Christmas worm

Given here is an overview analysis of the Father Christmas Worm, a computer worm that was released onto the DECnet Internet three days before Christmas 1988. The purpose behind the worm was to send an electronic mail message to all users on the computer system running the worm. The message was a Christmas greeting and was signed 'Father Christmas'. From the investigation, it was determined that the worm was released from a computer (node number 20597::) at a university in Switzerland. The worm was designed to travel quickly. Estimates are that it was copied to over 6,000 computer nodes. However, it was believed to have executed on only a fraction of those computers. Within ten minutes after it was released, the worm was detected at the Space Physics Analysis Network (SPAN), NASA's largest space and Earth science network. Once the source program was captured, a procedural cure, using the existing functionality of the computer operating systems, was quickly devised and distributed. A combination of existing computer security measures, the quick and accurate procedures devised to stop copies of the worm from executing, and the network itself, were used to rapidly provide the cure. These were the main reasons why the worm executed on such a small percentage of nodes. This overview of the analysis of the events concerning the worm is based on an investigation made by the SPAN Security Team and provides some insight into future security measures that will be taken to handle computer worms and viruses that may hit similar networks.

Green, James L.↗
DOE OSTI2021

An Overview of the Usefulness of Machine Learning Techniques on Network Packet Data

Understanding the health and behavior of a computer network allows for better network efficiency and security. We present an overview of various machine learning techniques for classifying network packet data via packet metadata. While some classical machine learning approaches achieve reasonable results, the most accurate classification can be achieved with deep learning. On the four data sets studied herein, a basic deep learning model achieved at or near 100\% classification accuracy. We also propose a method for determining variable importance as a means for potential transfer learning applications to classifying yet unseen network packet data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Network Penetration Testing and Research

This paper will focus the on research and testing done on penetrating a network for security purposes. This research will provide the IT security office new methods of attacks across and against a company's network as well as introduce them to new platforms and software that can be used to better assist with protecting against such attacks. Throughout this paper testing and research has been done on two different Linux based operating systems, for attacking and compromising a Windows based host computer. Backtrack 5 and BlackBuntu (Linux based penetration testing operating systems) are two different "attacker'' computers that will attempt to plant viruses and or NASA USRP - Internship Final Report exploits on a host Windows 7 operating system, as well as try to retrieve information from the host. On each Linux OS (Backtrack 5 and BlackBuntu) there is penetration testing software which provides the necessary tools to create exploits that can compromise a windows system as well as other operating systems. This paper will focus on two main methods of deploying exploits 1 onto a host computer in order to retrieve information from a compromised system. One method of deployment for an exploit that was tested is known as a "social engineering" exploit. This type of method requires interaction from unsuspecting user. With this user interaction, a deployed exploit may allow a malicious user to gain access to the unsuspecting user's computer as well as the network that such computer is connected to. Due to more advance security setting and antivirus protection and detection, this method is easily identified and defended against. The second method of exploit deployment is the method mainly focused upon within this paper. This method required extensive research on the best way to compromise a security enabled protected network. Once a network has been compromised, then any and all devices connected to such network has the potential to be compromised as well. With a compromised network, computers and devices can be penetrated through deployed exploits. This paper will illustrate the research done to test ability to penetrate a network without user interaction, in order to retrieve personal information from a targeted host.

Murphy, Brandon F.↗
DOE OSTI2023

Space-based quantum networks are an essential component of future architecture for distributed quantum computers and quantum-enhanced secure communication

Space-based quantum links show great promise for connecting and communicating between quantum computers over ultra-long distances without the high loss incurred through fiber. A successful US quantum satellite would require large investment, national priority, and a diverse set of expertise. But, it would deliver US-owned quantum links that would allow for quantum-enhanced secure communications and the ability to connect quantum computers over long distances.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

IT Security Support for the Spaceport Command Control Systems Development Ground Support Development Operations

Security is one of the most if not the most important areas today. After the several attacks on the United States, security everywhere was heightened from Airports to the communication among the military branches legionnaires. With advanced persistent threats (APTs) on the rise following Stuxnet, government branches and agencies are required, more than ever, to follow several standards, policies and procedures to reduce the likelihood of a breach. Attack vectors today are very advanced and are going to continue to get more and more advanced as security controls advance. This creates a need for networks and systems to be in an updated and secured state in a launch control system environment. FISMA is a law that is mandated by the government to follow when government agencies secure networks and devices. My role on this project is to ensure network devices and systems are in compliance with NIST, as outlined in FISMA. I will achieve this by providing assistance with security plan documentation and collection, system hardware and software inventory, malicious code and malware scanning and configuration of network devices i.e. routers and IDSsIPSs. In addition I will be completing security assessments on software and hardware, vulnerability assessments and reporting, conducting patch management and risk assessments. A guideline that will help with compliance with NIST is the SANS Top 20 Critical Controls. SANS Top 20 Critical Controls as well as numerous security tools, security software and the conduction of research will be used to successfully complete the tasks given to me. This will ensure compliance with FISMA and NIST, secure systems and a secured network. By the end of this project, I hope to have carried out stated above as well as gain an immense knowledge about compliance, security tools, networks and network devices, policies and procedures.

computer information security↗
DOE OSTI2018

Deep Learning for Unsupervised Insider Threat Detection in Structured Cyber Security Data Streams

Analysis of an organization's computer network activity is a key component of early detection and mitigation of insider threat, a growing concern for many organizations. Raw system logs are a prototypical example of streaming data that can quickly scale beyond the cognitive power of a human analyst. As a prospective filter for the human analyst, we present an online unsupervised deep learning approach to detect anomalous network activity from system logs in real time. Our models decompose anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat. Using the CERT Insider Threat Dataset v6.2 and threat detection recall as our performance metric, our novel deep and recurrent neural network models outperform Principal Component Analysis, Support Vector Machine and Isolation Forest based anomaly detection baselines. For our best model, the events labeled as insider threat activity in our dataset had an average anomaly score in the 95.53 percentile, demonstrating our approach's potential to greatly reduce analyst workloads.

Deep Learning, Insider Threat↗
DOE OSTI2017

R&D100 Finalist: Neuromorphic Cyber Microscope

The Neuromorphic Cyber Microscope provides security analysts with unprecedented visibility of their network, computer and storage assets. This processor is the world's first practical implementation of neuromorphic technology to a major computer science mission. Working with Lewis Rhodes Labs, engineers at Sandia National Laboratories have created a device that is orders of magnitude faster at analyzing data to identify cyber-attacks.

97 MATHEMATICS AND COMPUTING↗