Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Ant colony optimization (1)
- Automatic dependent surveillance-broadcast (1)
- Commercial Space Industry (1)
- Complex adaptive supply networks (1)
- Computer forensics (1)
-
- Convolutional network (1)
- Cyber Intrusion (1)
- Cyclone DDS (1)
- DDS (1)
- Distributed system (1)
- False injection (1)
- Field programmable gate arrays (1)
- Information theory (1)
- Internet telephony (1)
- Kerberos (1)
- Multi-agent system (1)
- Network Intrusion Detection System (1)
- Network anomaly (1)
- Network data (1)
- Open-source data (1)
- Peer to peer (1)
- Peer-to-peer computing (1)
- Performance benchmarking (1)
- QoS (1)
- RISC-V (1)
- Relevance testing (1)
- Reliability (Computer Sciences) (1)
- Safety (1)
- Satellite Control (1)
- Satellite Controll (1)
Articles 1 - 10 of 10
Full-Text Articles in Engineering
Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton *, Richard Dill, Michael R. Grimaila, Douglas Hodson
Ads-B Classification Using Multivariate Long Short-Term Memory–Fully Convolutional Networks And Data Reduction Techniques, Sarah Bolton *, Richard Dill, Michael R. Grimaila, Douglas Hodson
Faculty Publications
Researchers typically increase training data to improve neural net predictive capabilities, but this method is infeasible when data or compute resources are limited. This paper extends previous research that used long short-term memory–fully convolutional networks to identify aircraft engine types from publicly available automatic dependent surveillance-broadcast (ADS-B) data. This research designs two experiments that vary the amount of training data samples and input features to determine the impact on the predictive power of the ADS-B classification model. The first experiment varies the number of training data observations from a limited feature set and results in 83.9% accuracy (within 10% of …
Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry
Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry
Faculty Publications
Securing distributed device communication is critical because the private industry and the military depend on these resources. One area that adversaries target is the middleware, which is the medium that connects different systems. This paper evaluates a novel security layer, DDS-Cerberus (DDS-C), that protects in-transit data and improves communication efficiency on data-first distribution systems. This research contributes a distributed robotics operating system testbed and designs a multifactorial performance-based experiment to evaluate DDS-C efficiency and security by assessing total packet traffic generated in a robotics network. The performance experiment follows a 2:1 publisher to subscriber node ratio, varying the number of …
Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …
Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard A. Dill, Douglas D. Hodson
Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard A. Dill, Douglas D. Hodson
Faculty Publications
Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded …
Shifting Satellite Control Paradigms: Operational Cybersecurity In The Age Of Megaconstellations, Carl A. Poole [*], Robert A. Bettinger, Mark Reith
Shifting Satellite Control Paradigms: Operational Cybersecurity In The Age Of Megaconstellations, Carl A. Poole [*], Robert A. Bettinger, Mark Reith
Faculty Publications
The introduction of automated satellite control systems into a space-mission environment historically dominated by human-in-the-loop operations will require a more focused understanding of cybersecurity measures to ensure space system safety and security. On the ground-segment side of satellite control, the debut of privately owned communication antennas for rent and a move to cloud-based operations or mission centers will bring new requirements for cyber protection for both Department of Defense and commercial satellite operations alike. It is no longer a matter of whether automation will be introduced to satellite operations, but how quickly satellite operators can adapt to the onset of …
Sparc: Statistical Performance Analysis With Relevance Conclusions, Justin C. Tullos, Scott R. Graham, Jeremy D. Jordan, Pranav R. Patel
Sparc: Statistical Performance Analysis With Relevance Conclusions, Justin C. Tullos, Scott R. Graham, Jeremy D. Jordan, Pranav R. Patel
Faculty Publications
The performance of one computer relative to another is traditionally characterized through benchmarking, a practice occasionally deficient in statistical rigor. The performance is often trivialized through simplified measures, such as the approach of central tendency, but doing so risks a loss of perspective of the variability and non-determinism of modern computer systems. Authentic performance evaluations are derived from statistical methods that accurately interpret and assess data. Methods that currently exist within performance comparison frameworks are limited in efficacy, statistical inference is either overtly simplified or altogether avoided. A prevalent criticism from computer performance literature suggests that the results from difference …
Using Information-Theoretic Principles To Analyze And Evaluate Complex Adaptive Supply Network Architectures, Joshua V. Rodewald, John M. Colombi, Kyle F. Oyama, Alan W. Johnson
Using Information-Theoretic Principles To Analyze And Evaluate Complex Adaptive Supply Network Architectures, Joshua V. Rodewald, John M. Colombi, Kyle F. Oyama, Alan W. Johnson
Faculty Publications
Information-theoretic principles can be applied to the study of complex adaptive supply networks (CASN). Previous modeling efforts of CASN were impeded by the complex, dynamic nature of the systems. However, information theory provides a model-free approach to the problem removing many of those barriers. Understanding how principles such as transfer entropy, excess entropy/predictive information, information storage, and separable information apply in the context of supply networks opens up new ways of studying these complex systems. Additionally, these principles provide the potential for new business analytics which give managers of CASN new insights into the system's health, behavior, and eventual control …
An Fpga-Based System For Tracking Digital Information Transmitted Via Peer-To-Peer Protocols, Karl R. Schrader, Barry E. Mullins, Gilbert L. Peterson, Robert F. Mills
An Fpga-Based System For Tracking Digital Information Transmitted Via Peer-To-Peer Protocols, Karl R. Schrader, Barry E. Mullins, Gilbert L. Peterson, Robert F. Mills
Faculty Publications
This paper presents a Field Programmable Gate Array (FPGA)-based tool designed to process file transfers using the BitTorrent Peer-to-Peer (P2P) protocol and VoIP phone calls made using the Session Initiation Protocol (SIP). The tool searches selected control messages in real time and compares the unique identifier of the shared file or phone number against a list of known contraband files or phone numbers. Results show the FPGA tool processes P2P packets of interest 92% faster than a software-only configuration and is 97.6% accurate at capturing and processing messages at a traffic load of 89.6 Mbps.
Structured P2p Technologies For Distributed Command And Control, Daniel R. Karrels, Gilbert L. Peterson, Barry E. Mullins
Structured P2p Technologies For Distributed Command And Control, Daniel R. Karrels, Gilbert L. Peterson, Barry E. Mullins
Faculty Publications
The utility of Peer-to-Peer (P2P) systems extends far beyond traditional file sharing. This paper provides an overview of how P2P systems are capable of providing robust command and control for Distributed Multi-Agent Systems (DMASs). Specifically, this article presents the evolution of P2P architectures to date by discussing supporting technologies and applicability of each generation of P2P systems. It provides a detailed survey of fundamental design approaches found in modern large-scale P2P systems highlighting design considerations for building and deploying scalable P2P applications. The survey includes unstructured P2P systems, content retrieval systems, communications structured P2P systems, flat structured P2P systems and …
Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson
Network Formation Using Ant Colony Optimization -- A Systematic Review, Steven C. Oimoen, Gilbert L. Peterson, Kenneth M. Hopkinson
Faculty Publications
A significant area of research in the field of hybrid communications is the Network Design Problem (NDP) [1]. The NDP is an NP complete problem [1] that focuses on identifying the optimal network topology for transmitting commodities between nodes, under constraints such as bandwidth, limited compatible directed channels, and link and commodity costs. The NDP focuses on designing a flexible network while trying to achieve optimal flow or routing. If a link (or arc) is used, then an associated fixed cost of the edge is incurred. In addition, there is a cost for using the arc depending on the flow. …