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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 145 records · Page 8

TF9 Dataset Analysis

Incident Overview: In the time between November 2, 2019 and November 11, 2019, WheelByte was plagued by breaches in security. These insecurities led to breaches in customer data, company data, and even the death of an employee, Matthew Swift. They have launched an investigation into the company’s computer systems in hopes to find the root cause. We have been provided with the following artifacts from WheelByte: memory images, disk images, network packet captures, and emails. We have found multiple cyber-system attacks against WheelByte. Our investigation lasted from July 13th - August 3rd, 2023. WheelByte allowed us to look at any and every file, and there were no restrictions on what we could or could not use in our investigation. By the end of our investigation, we have been able to deduce who is behind the attack, what they have done, and why they did it. A company that is closely related to WheelByte is called Slyde. Slyde sells electric scooters and it is known that the Chief Executive Officer (CEO) of Slyde, Kimberly Holmes, sees WheelByte as a threat to business, as Wheelbyte sells electric skateboards. We have been able to deduce that Slyde is likely behind many of the malicious attacks. We have seen exfiltration addresses to Slyde domains, along with other Slyde information within their malware. We can see lots of traffic to and from Slyde Internet Protocol (IP) addresses. This may be an attempt to cripple WheelByte’s productivity to remove Slyde’s competitor from the market.

97 MATHEMATICS AND COMPUTING↗

Energy Delivery Systems with Verifiable Trustworthiness (Final Report)

Energy Delivery Systems (EDS) must be verified to be free from intrusive and malicious software. One way of verifying this software is to perform device scans to detect malicious code. Because it is possible to have “fileless” malware that exists only in device (volatile) memory, offline scanning and even many forms of online scanning is insufficient for detection. This project (“Verify”) addresses this need by performing direct sampling of memory during device operation to detect unexpected or modified software while not interfering with device operation. The Verify project provides a proof-of-concept of detection by random sampling combined with remote software- and timing-based attestation methods for robust detection of in-memory threats. An external review of Verify was performed by our partner, General Electric (GE), and a summary of their findings is provided.

97 MATHEMATICS AND COMPUTING↗

FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests

Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.

97 MATHEMATICS AND COMPUTING↗

Countering Weapons of Mass Destruction Office (CWMD) Data Categorization Study: Chemical, Biological, Radiological, and Nuclear (CBRN) Detection Device Data

Pacific Northwest National Laboratory (PNNL) seeks to address critical questions related to chemical, biological, radiological, and nuclear (CBRN) detection devices. This research aims to enhance the security and understanding of these devices by investigating various aspects of their identification, communication, and functionality. The primary focus is on network security, malware detection, device identification, and intelligence gathering. CBRN data can be categorized in various ways depending on the purpose of CBRN detection devices and the specific context of the applications for analysis. Criteria that can be used to assist in this effort include but are not limited to data type, data protocol, source/destination, application, time, security, and content. This study will inform additional paths for data classification, data profiling, data mapping, and data modeling. This will help the Countering Weapons of Mass Destruction Office (CWMD) better understand their data and make informed decisions based on the insights gained from this study and their application. The CBRN Data Categorization study will include the identification of 5–10 different CBRN detection devices with unique characteristics for assessing and analyzing the data that is being produced by and transmitted from these devices.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Resilience Through Data-Driven, Intelligent Designed Control: A Formal Methods Approach

The PNNL and GTRI team developed a strategy to integrate temporal logic rule specification for detection of cyber-intrusion in the source code and control algorithms of CPS using advanced cyber-data. The GTRI team utilized its capabilities in rule synthesis and temporal logic specifications for software assurance and verification to detect and predict impact of cyber-intrusions and malware in the computational and control algorithms of cyber-physical systems. The team also developed a testing and verification approach that could be used to validate the suggested approach against a realistic use-case CPS showcasing improvements in system impact prediction performance. Temporal logic offers a compact expression of events in absolute and relative time and has a formalized translation to state machines. As such, temporal logic rules can feasibly be synthesized to any system as a rule engine, with the process being formally verified to be correct. The goal here is to utilize temporal logic rules to detect cyber-attacks and manipulations in the computational algorithms and provide real-time software assurance and verification guarantees.

97 MATHEMATICS AND COMPUTING↗

Precursor Analysis Report: Doppelpaymer Ransomware Attack on Petroleos Mexicanos (PEMEX) 2019

The DoppelPaymer Ransomware Attack on Petroleos Mexicanos (PEMEX) 2019 Precursor Analysis Report leverages publicly available information about the PEMEX cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The 2019 DoppelPaymer ransomware attack on PEMEX, Mexico’s nationalized petroleum corporation, highlights a unique threat that ransomware and cybercriminal extortion poses to Operational Technology (OT) environments in critical infrastructure. The incident began with an employee downloading commodity malware that allowed adversaries to gain initial access to PEMEX’s enterprise environment. After conducting privilege escalation, tool ingress, and data exfiltration, the adversaries deployed DoppelPaymer ransomware throughout the PEMEX enterprise environment, resulting in the company having to take dozens of systems offline for at least several days. Although PEMEX stated that their operations were not affected, the data exfiltrated from PEMEX was made available for download on DoppelPaymer’s leak site, as well as on other illicit criminal forums. This stolen data included not only company information, but also sensitive OT-specific configuration data. This incident showcases how cybercriminal exfiltration and posting of sensitive OT architecture documentation can pose security concerns for the targeted organization for years due to the long lifespan of OT assets and architectures. Researchers and analysts identified 18 unique techniques utilized during the attack with a total of 190 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Fifteen of the identified techniques used during the DoppelPaymer ransomware attack were precursors to the triggering event. Analysis identified 163 observables associated with these precursor techniques, 34 of which were assessed to have an increased likelihood of being perceived in the 60 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Anatomy of a Security Operations Center

Many agencies and corporations are either contemplating or in the process of building a cyber Security Operations Center (SOC). Those Agencies that have established SOCs are most likely working on major revisions or enhancements to existing capabilities. As principle developers of the NASA SOC; this Presenters' goals are to provide the GFIRST community with examples of some of the key building blocks of an Agency scale cyber Security Operations Center. This presentation viII include the inputs and outputs, the facilities or shell, as well as the internal components and the processes necessary to maintain the SOC's subsistence - in other words, the anatomy of a SOC. Details to be presented include the SOC architecture and its key components: Tier 1 Call Center, data entry, and incident triage; Tier 2 monitoring, incident handling and tracking; Tier 3 computer forensics, malware analysis, and reverse engineering; Incident Management System; Threat Management System; SOC Portal; Log Aggregation and Security Incident Management (SIM) systems; flow monitoring; IDS; etc. Specific processes and methodologies discussed include Incident States and associated Work Elements; the Incident Management Workflow Process; Cyber Threat Risk Assessment methodology; and Incident Taxonomy. The Evolution of the Cyber Security Operations Center viII be discussed; starting from reactive, to proactive, and finally to proactive. Finally, the resources necessary to establish an Agency scale SOC as well as the lessons learned in the process of standing up a SOC viII be presented.

Wang, John↗

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↗

IT Security Support for the Spaceport Command Control System Development

My job title is IT Security support for the Spaceport Command & Control System Development. As a cyber‐security analyst it is my job to ensure NASA's information stays safe from cyber threats, such as, viruses, malware and denial-of-service attacks by establishing and enforcing system access controls. Security is very important in the world of technology and it is used everywhere from personal computers to giant networks ran by Government agencies worldwide. Without constant monitoring analysis, businesses, public organizations and government agencies are vulnerable to potential harmful infiltration of their computer information system. It is my responsibility to ensure authorized access by examining improper access, reporting violations, revoke access, monitor information request by new programming and recommend improvements. My department oversees the Launch Control System and networks. An audit will be conducted for the LCS based on compliance with the Federal Information Security Management Act (FISMA) and The National Institute of Standards and Technology (NIST). I recently finished analyzing the SANS top 20 critical controls to give cost effective recommendations on various software and hardware products for compliance. Upon my completion of this internship, I will have successfully completed my duties as well as gain knowledge that will be helpful to my career in the future as a Cyber Security Analyst.

IT Security↗

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 has heightened from airports to the communication among the military branches legionnaires. With advanced persistent threats (APT's) 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 IDS's/IPS's. In addition, I will be completing security assessments on software and hardware, vulnerability assessments and reporting, and 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 the tasks stated above as well as gain an immense knowledge about compliance, security tools, networks and network devices, as well as policies and procedures.

security↗

IT Security Support for Spaceport Command and Control System

During the fall 2013 semester, I worked at the Kennedy Space Center as an IT Security Intern in support of the Spaceport Command and Control System under the guidance of the IT Security Lead Engineer. Some of my responsibilities included assisting with security plan documentation collection, system hardware and software inventory, and malicious code and malware scanning. Throughout the semester, I had the opportunity to work on a wide range of security related projects. However, there are three projects in particular that stand out. The first project I completed was updating a large interactive spreadsheet that details the SANS Institutes Top 20 Critical Security Controls. My task was to add in all of the new commercial of the shelf (COTS) software listed on the SANS website that can be used to meet their Top 20 controls. In total, there are 153 unique security tools listed by SANS that meet one or more of their 20 controls. My second project was the creation of a database that will allow my mentor to keep track of the work done by the contractors that report to him in a more efficient manner by recording events as they occur throughout the quarter. Lastly, I expanded upon a security assessment of the Linux machines being used on center that I began last semester. To do this, I used a vulnerability and configuration tool that scans hosts remotely through the network and presents the user with an abundance of information detailing each machines configuration. The experience I gained from working on each of these projects has been invaluable, and I look forward to returning in the spring semester to continue working with the IT Security team.

computer security↗

Akatosh: Automated Cyber Incident Verification and Impact Analysis

Akatosh is a highly configurable system based on the integration of the capabilities of one or more Intrusion Detection Systems (IDS) and automated forensic analysis. Akatosh reduces the false positive rates of IDSs and alleviates costs of incident response by pointing forensic personnel to the root cause of an incident on affected endpoint devices. Akatosh is able to analyze a computer system in near real-time and provide operations and forensic analyst personnel with continuous feedback on the impact of malware and software on deployed systems. Additionally, Akatosh provides the ability to look back into any prior state in the history of the computer system along with the ability to compare one or more prior system states with any other prior state.

Smith, Jared M↗

Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. As a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.

Apache Spark↗

Behavior specification, finding main, and call graph visualizations

A process transforms compiled software into a semantic form. The process transforms the code into a semantic form. The process analyzes behavior functionality by processing precise programming behavior abstractions stored in a memory and classifies the code as malware based on the code behavior. Another method identifies the starting point of execution of a compiled program. The method calculates a complexity measure by calculating the number of potential execution paths of local functions; identifies the number of arguments passed to local functions; and identifies the starting point of execution of the compiled program. Another method provides interactive, dynamic visualization of a group of related functions wherein a user can explore the rendered graph and select a specific function and display functions that are color coded by their ancestral relation and their function call distance to the selected function.

97 MATHEMATICS AND COMPUTING↗

Software classification using phylogenetic techniques

Software, such as malware, may be classified using phylogenetic techniques. An evolutionary history of a representative set of software programs may be reconstructed to generate a reference phylogeny. Dynamic traces of the representative software programs may be obtained. The dynamic traces may include time-ordered sequences of execution commands extracted from running software binaries. Metrics may be developed using the dynamic traces. One or more unknown software programs may then be classified against the reference phylogeny using the metrics developed using the dynamic traces of the representative set of software programs.

97 MATHEMATICS AND COMPUTING↗

Assembling a Cyber Range to Evaluate Artificial Intelligence / Machine Learning (AI/ML) Security Tools

In this case study, we will describe the design and assembly of a cyber security test range we have built at Oak Ridge National Laboratory in Oak Ridge, TN, USA. The range is designed to provide a flexible environment to evaluate cyber security tools—particularly those involving AI/ML—in a way that provides realistic environments and where we can control the experiments to determine the strengths and weaknesses of the tools. We have designed in the ability to repeat the evaluations, so additional tools can be evaluated and compared at a later time. The system is one that can be scaled up or down for experiment sizes. At the time of the conference we will have completed two full-scale, national, government challenges on this range. These challenges are evaluating the performance and operating costs for AI/ML-based cyber security tools for application into large, government-sized environments. These evaluations will be described, in order to provide motivation and context for various design decisions and adaptations we have made. The first challenge measured end-point security tools against 100K malware samples chosen across a range of types. The second is network detection of attempted penetration and exploitations with varying levels of covertness in a high-volume, business network. The scale of each of these challenges is requiring us to create automation systems to repeat the experiments identically for each tool. Preventing there being easy signs of malicious activity for the AI/ML tools to focus on has been a particularly interesting and challenging aspect of designing and executing these challenge events. After the events, the range continues to be used for other research such as adversarial machine learning where the repeatability, scale, and automation required for the national challenge events become essential elements for research.

Nichols, Jeff↗

Automated Threat Information Generation

Manual malware analysis is time consuming and is not scalable. This poster describes tools that INL has developed that automate and codify threat information.

99 GENERAL AND MISCELLANEOUS↗

Implications of the 2015 and 2016 Ukrainian electric grid cyber attacks to nuclear power plants - 113

Nuclear plants can be vulnerable from electric grid cyber attacks. In December 2015 and December 2016, cyber attackers attacked the Ukrainian electric grid and 'turned off the lights' by opening substation protective relays. The 2015 cyber attacks targeted electric distribution systems and the 2016 cyber attacks targeted electric transmission systems. In order to accomplish the attacks, the cyber attackers compromised field control system devices to inject malware and then open protective relays in substations. There are some very significant implications to nuclear plant operations from hacking the substations and switchyard breakers that serve nuclear plants. The nuclear plant operational concerns are compromising protective relays to prevent relay protection that would result in damage to large electric equipment; spurious actuation of protective relays causing loss-of-offsite power (LOOP) conditions; and the closing and then reopening of protective relays out-of-phase with the grid causing the Aurora vulnerability damaging generators, Alternating Current (AC) motors, and transformers. All of these protective relay conditions have already occurred in actual or test conditions. The common thread to these scenarios are that switchyard and substation protective relays are out-of-scope of existing nuclear cyber security regulations yet, when compromised, have demonstrated impacts to nuclear plant operations and challenged safety systems. There is one other issue about an attack originating from a protective relay. That is, it would be irrelevant whether the nuclear plant system that would be impacted would have analog or digital instrumentation and control (I and C) systems because the impact is upstream of the I and C. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗