OS and Networks Commons^™

Using Siamese Neural Networks To Effectively Detect Trojans In Fpgas When Trojans Manipulate Encryption Operations At The Bitstream Level, Kylie Arnett

Graduate Theses and Dissertations (2019 - present)

This research investigates security vulnerabilities in Field-Programmable Gate Arrays (FPGAs) at the bitstream level, focusing on hardware trojans (HTs) that manipulate encryption operations. This study addresses two critical questions: (1) The feasibility of exploiting FPGA bitstreams to selectively bypass encryption operations when a predefined input pattern is observed (all ones), thereby exposing sensitive data, and (2) the efficacy of Siamese Neural Networks (SNNs) in detecting such trojans with high accuracy. FPGAs are vulnerable to malicious modifications during manufacturing or deployment, posing risks to data integrity and system functionality. In this work, a trojan is inserted into a Xilinx series-7 FPGA …

Integrating Nonlinear Phase Space Analysis And Image-Based Representation For Network Intrusion Detection, Chakriya Suon

Shelby Hall Graduate Research Forum Posters

With the rise of cyber threats, cybersecurity continues to play a critical role in the ever-changing landscape of technology by protecting and defending against threat agents. Our research applies novel machine learning (ML)techniques to detect network intrusions effectively. Our primary focus is to extend prior research, which has used network flows that are processed by a nonlinear phase space algorithm (NLPSA). The NLSPA approach has proven extremely effective in detecting anomalous or malicious traffic patterns on representative data but requires extensive training time.

Our contribution integrates deep learning into the anomaly detection approach by creating image-based representations of the adjacency …

Nonlinear Phase Space Analysis For Anomaly Detection In Ros 2 Communications: Detecting Man-In-The-Middle Attacks In Simulated Environments, William L. Locklier

Graduate Theses and Dissertations (2019 - present)

Robot Operating System 2 (ROS 2) marks a significant advancement over its predecessor through the transition from a centralized to a decentralized architecture, integrating the Data Distribution Service (DDS) to support real-time, scalable communications. Despite these improvements, inherent vulnerabilities in the ROS 2 communication stack continue to leave these systems exposed to sophisticated network-based attacks. This study leveraged nonlinear phase space analysis (NLPSA) as an intrusion detection system (IDS) to detect man-in-the-middle (MitM) attack anomalies in ROS 2 traffic. Grounded in Takens’ embedding theorem, NLPSA reconstructs the phase space of communication features and compares the resulting structure against a baseline …

Out-Of-Band Anomaly Detection For Real Time Operating Systems, Jeffrey K. Holifield

Graduate Theses and Dissertations (2019 - present)

Real Time Operating Systems (RTOS) are increasing present throughout the industrial, business, defense, and healthcare spaces. These lightweight and efficient operating systems are designed to run on embedded, resource constrained devices, often within cyber-physical systems (CPS). A defining characteristic ofRTOSs is that they are deterministic. Tasks are scheduled to run on fixed timelines within guaranteed execution windows. In Industry 4.0 applications for example, sensors must receive and process inputs within a fixed schedule to ensure products are properly manufactured. This requires guaranteed service at fixed time periods. To accomplish this, RTOSs must conform to worst case execution times (WCETs) as …

Comparative Analysis Of Classical And Machine Learning Pathfinding Approaches, Miguel Gapud

Honors Theses

Pathfinding is an essential task for any autonomous robot. Graph-based classical pathfinding algorithms and machine learning approaches have both been used for this end, but they are often not compared against each other. An implementation of end-to-end (E2E) pathfinding using Proximal Policy Optimization (PPO) and an Alexnet architecture is compared against an implementation of Hybrid A*. A digital twin in Unity3D is used as the testing environment with the Clearpath Dingo as the pathfinding robot. In machine learning, the robot is controlled using PPO through ROS-Noetic with a camera as its sensor. Hybrid A* and its controls are implemented directly …

36 - Investigation Of The Digital Footprint Of Scientific Research In Social Media – Preliminary Findings, Lee Logan, Dominik Soos, Sean Baker, Jian Wu

Undergraduate Research Symposium

Title: Investigation of The Digital Footprint of Scientific Research in Social Media – Preliminary Findings

Authors: Lee Logan, Sean Baker, Dominik Soos, Jian Wu

The spread of scientific information and research beyond the confines of academic institutions plays a central role in how the public understands and trusts modern sciences. Social media has become an essential means of dissemination for scholarly news, papers, and other forms of engagement. This research aims to explore how scientific research is disseminated over social media to understand its role as a bridge between peer-reviewed research and the public's overall understanding. To support the research …

Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano

Shelby Hall Graduate Research Forum Posters

Our research presents a novel approach for turbulence prediction in computational fluid dynamics (CFD) simulations using a non-linear phase space analysis (NLPSA) and threshold algorithm. NLPSA has been utilized in medical applications to predict seizures, as well as in cybersecurity to detect malicious control and utilization of computing systems. NLPSA uses time-series data to learn the normal operating state of the system, then sets a threshold to predict when the system becomes abnormal. Turbulence prediction is similar, such that a fluid system changes from normal to abnormal. Turbulence prediction methods currently utilize machine learning tools, such as convolutional neural networks …

Out-Of-Band Anomaly Detection For Real Time Operating Systems, Jeff K. Holifield

Shelby Hall Graduate Research Forum Posters

Real Time Operating Systems (RTOS) are increasing present throughout the industrial, business, defense, and healthcare spaces. These lightweight and efficient operating systems are designed to run on embedded, resource constrained devices, often within cyber-physical systems (CFS). A defining characteristic of RTOSs is that they are deterministic. Tasks are scheduled to run on fixed timelines within guaranteed execution windows. To accomplish tasks on time, real time software must conform to worst case execution times (WCETs) as design parameters. WCET is the maximum time a particular task can take to complete. Exceeding the WCET could cause system failure and lead to damage, …

Using Machine Learning Models To Improve The Cyber Physical Security Of Drones, Sean Lee, Aviv Segev

Shelby Hall Graduate Research Forum Posters

This research proposes a new manner of implementing machine learning models such that, when applied on a drone, it will be able to accurately identify and maintain the authenticity of the entity sending the control data to the drone. To begin with, the drone will, for a pre-determined amount of signals received per unit time, determine the average signal strength (RSSI) of them and use that average to determine the approximate distance between the drone and the source of those signals. This single data point will be fed into a custom implementation of the SCluStream algorithm (a real-time clustering machine …

Computing In The Commonwealth: Specialized Education In Computer Science And Information Technology For High School Students In Virginia – An Environmental Scan, Amy Corning, Jonathan D. Becker, Jon Graham, James Carrigan, Keisha Tennessee

ICRE Publications

Over the past two decades, Virginia has invested substantially in STEM education, in part through specialized programs focused on computer science and information technology (CS/IT). This study represents the first effort to identify Virginia’s specialized secondary CS/IT programs and examine them collectively. Findings from the statewide environmental scan indicate that the programs are delivered through a wide variety of institutional structures, including Governor’s STEM Academies, Governor’s Schools, specialty centers, and academies, but most often through Career and Technical Education (CTE) centers. Programs tend to be concentrated in metropolitan areas, and some rural divisions may not be served. The programs provide …

Open-Source Forensics Tools Are Great Tools For Critical Used Machines, Erik Herrera

Electronic Theses and Dissertations

Open-Source software exists on everything from operating systems to daily productivity applications. In digital forensics, a very popular tool that is used to learn on and expand is Autopsy. Autopsy is known in the digital world due to its potential and wide usage. It is in many built packages of software inside the open-source world of applications. It is built into premade operating systems that are involved in Digital Forensics and Penetration Testing. Prebuilt OS includes Kali Linux and Computer Aided Investigative Environment (CAINE).

In the application to defend Open-Source software being just as good as closed-source software, I will …

Attribute-Based Fine-Grained Access Control Using Verifiable Credentials, Srinivasa Dumpa

Student Theses

In the era of digital transformation, ensuring secure and privacy-preserving access control mechanisms is of paramount importance. Traditional identity-based access control systems often fall short in providing granular control and user autonomy over digital identities. This thesis presents a novel approach to access control by leveraging the power of verifiable credentials and attribute-based access control. The proposed system introduces a decentralized and user-centric framework that enables fine-grained access control based on specific attributes encapsulated within verifiable credentials. These tamper-evident digital credentials, stored in a user's digital wallet, contain a rich set of attributes that can be selectively disclosed to grant …

Interpretable Learning In Multivariate Big Data Analysis For Network Monitoring, José Camacho, Katarzyna Wasielewska, Rasmus Bro, David Kotz

Dartmouth Scholarship

There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it cannot be interpreted by a human operator. In this paper, we present an extension of the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool. In this extension, we propose a solution to the automatic derivation of features, a cornerstone step for the application of MBDA when the amount of data is massive. The resulting network monitoring approach allows …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

A Multimodal Immune System Inspired Defense Architecture For Detecting And Deterring Digital Pathogens In Container Hosted Web Services, Islam Khalil

Theses and Dissertations

With the increased use of web technologies, microservices, and Application Programming Interface (API) for integration between systems, and with the development of containerization of services on operating system level as a method of isolating system execution and for easing the deployment and scaling of systems, there is a growing need as well as opportunities for providing platforms that improve the security of such services. In our work, we propose an architecture for a containerization platform that utilizes various concepts derived from the human immune system. The goal of the proposed containerization platform is to introduce the concept of slowing down …

Linux Malware Obfuscation, Brian Roden

Computer Science and Computer Engineering Undergraduate Honors Theses

Many forms of malicious software use techniques and tools that make it harder for their functionality to be parsed, both by antivirus software and reverse-engineering methods. Historically, the vast majority of malware has been written for the Windows operating system due to its large user base. As such, most efforts made for malware detection and analysis have been performed on that platform. However, in recent years, we have seen an increase in malware targeting servers running Linux and other Unix-like operating systems resulting in more emphasis of malware research on these platforms. In this work, several obfuscation techniques for Linux …

Interpretable Learning In Multivariate Big Data Analysis For Network Monitoring, José Camacho, Rasmus Bro, David Kotz

Dartmouth Scholarship

There is an increasing interest in the development of new data-driven models useful to assess the performance of communication networks. For many applications, like network monitoring and troubleshooting, a data model is of little use if it cannot be interpreted by a human operator. In this paper, we present an extension of the Multivariate Big Data Analysis (MBDA) methodology, a recently proposed interpretable data analysis tool. In this extension, we propose a solution to the automatic derivation of features, a cornerstone step for the application of MBDA when the amount of data is massive. The resulting network monitoring approach allows …

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Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu

College of Sciences Posters

Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …

A Secure And Distributed Architecture For Vehicular Cloud And Protocols For Privacy-Preserving Message Dissemination In Vehicular Ad Hoc Networks, Hassan Mistareehi

Theses and Dissertations--Computer Science

Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can …

Defense Of A Small Network, Isabella Adkins

Williams Honors College, Honors Research Projects

A sample network will be virtually created consisting of three routers, one switch, and three hosts. The network will be secured using various methods such as enabling passwords and encryption. After the network has been properly secured, various attacks will be attempted with the goal of breaking into the network. These attacks include reconnaissance (gathering information), penetrating the network using the tool Metasploit, and attempting to get a credential phishing email to end users. If successful in the attacks, the network will be revisited and analyzed for any weaknesses or oversights.

A Different Way To Penetrate Nba Defenses, Trey Trucksis

Williams Honors College, Honors Research Projects

This project proposal will document the design, configuration, and penetration testing of a network consisting of three routers (labeled as Lakers, Celtics, Cavaliers), one switch (labeled as NBA), and three end devices (labeled as Kali, Windows 10, and Ubuntu) each connected to one of three routers present on the network. Each router will be attached to a different subnet on the network. The network will be secured using encrypted passwords on the router interfaces, OSPF MD5 authentication between the routers, port security on the switch, as well as Access Control Lists to to control the privileges of each subnetwork accordingly. …

Small Business Office Network, Michael Gerome

Williams Honors College, Honors Research Projects

This project will emulate a small office network environment. The project will demonstrate the process of building and configuring the network to meet the requirements laid out in the project plan. This network includes four subnets with Windows 10 end devices and a Kali Linux device, it also includes five Cisco layer 2 switches and three Cisco routers. There are also three subnets connecting the routers to each other to enable routing between the subnets. After the network environment is set up, various penetration tests are performed from the Kali Linux device to gather information. The Nmap reconnaissance tool is …

Automated Evaluation For Distributed System Assignments, Nimesh Nischal

Master's Projects

A distributed system can exist in numerous states, including many erroneous permutations that could have been addressed in the code. As distributed systems such as cloud computing and microservices gain popularity, involving distributed com- puting assignments is becoming increasingly crucial in Computer Science and related fields. However, designing such systems poses various challenges, such as considering parallel executions, error-inducing edge cases, and interactions with external systems. Typically, distributed assignments require students to implement a system and run multiple instances of the same code to behave as distributed. However, such assign- ments do not encourage students to consider the potential edge …

Ubiquitous Application Data Collection In A Disconnected Distributed System, Deepak Munagala

Master's Projects

Despite some incredible advancements in technology, a significant population of the world does not have internet connectivity. These people lack access to crucial information that is easily available to the rest of the world. To solve this problem, we implement a Delay Tolerant Network (DTN) that allows users in disconnected regions access to the internet. This is enabled by collecting all data requests on the users’ phones and passing them to a device that can carry them to a connected region. This device can then collect the necessary information and give it back to the users in the disconnected region. …

Probing Conformational Landscapes And Mechanisms Of Allosteric Communication In The Functional States Of The Abl Kinase Domain Using Multiscale Simulations And Network-Based Mutational Profiling Of Allosteric Residue Potentials, Keerthi Krishnan, Hao Tian, Peng Tao, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with …

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Coded Distributed Function Computation, Pedro J. Soto

Dissertations, Theses, and Capstone Projects

A ubiquitous problem in computer science research is the optimization of computation on large data sets. Such computations are usually too large to be performed on one machine and therefore the task needs to be distributed amongst a network of machines. However, a common problem within distributed computing is the mitigation of delays caused by faulty machines. This can be performed by the use of coding theory to optimize the amount of redundancy needed to handle such faults. This problem differs from classical coding theory since it is concerned with the dynamic coded computation on data rather than just statically …

Two Project On Information Systems Capabilities And Organizational Performance, Giridhar Reddy Bojja

Masters Theses & Doctoral Dissertations

Information systems (IS), as a multi-disciplinary research area, emphasizes the complementary relationship between people, organizations, and technology and has evolved dramatically over the years. IS and the underlying Information Technology (IT) application and research play a crucial role in transforming the business world and research within the management domain. Consistent with this evolution and transformation, I develop a two-project dissertation on Information systems capabilities and organizational outcomes.

Project 1 examines the role of hospital operational effectiveness on the link between information systems capabilities and hospital performance. This project examines the cross-lagged effects on a sample of 217 hospitals measured over …

Malware And Memory Forensics On M1 Macs, Charles E. Glass

LSU Master's Theses

As malware continues to evolve, infection mechanisms that can only be seen in memory are increasingly commonplace. These techniques evade traditional forensic analysis, requiring the use of memory forensics. Memory forensics allows for the recovery of historical data created by running malware, including information that it tries to hide. Memory analysis capabilities have lagged behind on Apple's new M1 architecture while the number of malicious programs only grows. To make matters worse, Apple has developed Rosetta 2, the translation layer for running x86_64 binaries on an M1 Mac. As a result, all malware compiled for Intel Macs is theoretically functional …