Engineering Commons^™

Cyber Risks In Ontario Online Elections, James D. Brunet

Electronic Thesis and Dissertation Repository

Online voting is increasingly prevalent in Ontario's municipalities, despite a lack of regulated technological and procedural safeguards. Individual municipalities, lacking deep knowledge of online voting technologies, are responsible for procuring technology from private vendors which make security and privacy claims that are difficult to verify. These reasons, among others, have contributed to an anomalous environment where election technology, security, and procedures diverge greatly from other robust democracies that use electronic voting. This thesis demonstrates this divergence by first presenting a novel security vulnerability in a popular online voting system used in Ontario, as well as the difficulty communicating this risk …

Comprehensive Network Redundancy Implementation And Cybersecurity Hardening Project: Ensuring Resilience And Defending Against Dhcp Starvation, Stp Man-In-The-Middle, And Brute Force Attacks, Seth Shaheen

Williams Honors College, Honors Research Projects

I have created a network topology that contains three Cisco routers, three Cisco switches, and three endpoints. The network has been built using the software GNS-3. The endpoints on the topology include one VPC, one Kali Linux VM, and one Ubuntu Server VM. The main purpose of this network topology is to show the skills I have learned during my tenure at The University of Akron. This will be done by hardening this network to ensure that the network is impervious to cyber-attacks. The Kali Linux VM will act as the attacker on the network and conduct three attacks: STP …

The Next Threat Landscape: Securing America’S Cyber-Physical Systems, Grayson Thomas

Honors College Theses

The goal of this research is to explore, identify, and enumerate the security threats that exist to industry current industrial controls systems (ICS) and supervisory control and data acquisition systems (SCADA). A scale lab similar to industry standard will be built and developed for research purposes. The Purdue Model for ICS and the Cyber Kill Chain will be referenced as frameworks for attack sequences, and the MITRE ATT&CK framework will be referenced for attack types. Attempts will be made to compromise the various pieces of our built SCADA system via configuration errors, software vulnerabilities, and deployment mistakes common with industrial …

Enhancing Cyber Resilience: Development, Challenges, And Strategic Insights In Cyber Security Report Websites Using Artificial Inteligence, Pooja Sharma

Harrisburg University Dissertations and Theses

In an era marked by relentless cyber threats, the imperative of robust cyber security measures cannot be overstated. This thesis embarks on an in-depth exploration of the historical trajectory and contemporary relevance of penetration testing methodologies, elucidating their evolution from nascent origins to indispensable tools in the cyber security arsenal. Moreover, it undertakes the ambitious task of conceptualizing and implementing a cyber security report website, meticulously designed to fortify cyber resilience in the face of ever-evolving threats in the digital realm.

The research journey commences with an insightful examination of the historical antecedents of penetration testing, tracing its genesis in …

Cyber Attacks Against Industrial Control Systems, Adam Kardorff

LSU Master's Theses

Industrial Control Systems (ICS) are the foundation of our critical infrastructure, and allow for the manufacturing of the products we need. These systems monitor and control power plants, water treatment plants, manufacturing plants, and much more. The security of these systems is crucial to our everyday lives and to the safety of those working with ICS. In this thesis we examined how an attacker can take control of these systems using a power plant simulator in the Applied Cybersecurity Lab at LSU. Running experiments on a live environment can be costly and dangerous, so using a simulated environment is the …

Cybersecurity In Critical Infrastructure Systems: Emulated Protection Relay, Mitchell Bylak

Computer Science and Computer Engineering Undergraduate Honors Theses

Cyber-attacks on Critical Systems Infrastructure have been steadily increasing across the world as the capabilities of and reliance on technology have grown throughout the 21st century, and despite the influx of new cybersecurity practices and technologies, the industry faces challenges in its cooperation between the government that regulates law practices and the private sector that owns and operates critical infrastructure and security, which has directly led to an absence of eas- ily accessible information and learning resources on cybersecurity for use in public environments and educational settings. This honors research thesis addresses these challenges by submitting the development of an …

Sel4 On Risc-V - Developing High Assurance Platforms With Modular Open-Source Architectures, Michael A. Doran Jr

Masters Theses

Virtualization is now becoming an industry standard for modern embedded systems. Modern embedded systems can now support multiple applications on a single hardware platform while meeting power and cost requirements. Virtualization on an embedded system is achieved through the design of the hardware-software interface. Instruction set architecture, ISA, defines the hardware-software interface for an embedded system. At the hardware level the ISA, provides extensions to support virtualization.

In addition to an ISA that supports hypervisor extensions it is equally important to provide a hypervisor completely capable of exploiting the benefits of virtualization for securing modern embedded systems. Currently there does …

Detection Of Crypto-Ransomware Attack Using Deep Learning, Muna Jemal

Master of Science in Computer Science Theses

The number one threat to the digital world is the exponential increase in ransomware attacks. Ransomware is malware that prevents victims from accessing their resources by locking or encrypting the data until a ransom is paid. With individuals and businesses growing dependencies on technology and the Internet, researchers in the cyber security field are looking for different measures to prevent malicious attackers from having a successful campaign. A new ransomware variant is being introduced daily, thus behavior-based analysis of detecting ransomware attacks is more effective than the traditional static analysis. This paper proposes a multi-variant classification to detect ransomware I/O …

Protecting The Infrastructure Of Michigan: Analyzing And Understanding Internet Infrastructure, Samuel Blaser, Travis Munyer, Damian Ramirez, Lester Juarez, Jackson Servant

Theses/Capstones/Creative Projects

The Michigan Army National Guard DCOE is hoping to increase their understanding of the physical, electrical, protocol, and logical topography of internet service. In order to understand the infrastructure of the internet, information must be collected on its pieces. By studying, describing, and illustrating the infrastructure of the global internet we can develop hardening tactics, improve user training, and develop contingency plans in the case of an attack. The research is focused on where data lives, locating data centers in the region, identifying global infrastructure and who owns it, and potential for hardening. An interactive map has been created in …

Bridging The Gap Between Public Organizaions And Cybersecurity, Christopher Boutros

Electronic Theses, Projects, and Dissertations

Cyberattacks are a major problem for public organizations across the nation, and unfortunately for them, the frequency of these attacks is constantly growing. This project used a case study approach to explore the types of cybersecurity public organization agencies face and how those crimes can be mitigated. The goal of this paper is to understand how public organization agencies have prepared for cyberattacks and discuss additional suggestions to improve their current systems with the current research available This research provides an analysis of current cyber security systems, new technologies that can be implemented, roadblocks public agencies face before and during …

Enhancing Cyberspace Monitoring In The United States Aviation Industry: A Multi-Layered Approach For Addressing Emerging Threats, Matthew Janson

Doctoral Dissertations and Master's Theses

This research project examined the cyberspace domain in the United States (U.S.) aviation industry from many different angles. The research involved learning about the U.S. aviation cyberspace environment, the landscape of cyber threats, new technologies like 5G and smart airports, cybersecurity frameworks and best practices, and the use of aviation cyberspace monitoring capabilities. The research looked at how vulnerable the aviation industry is from cyber-attacks, analyzed the possible effects of cyber-attacks on the industry, and suggests ways to improve the industry's cybersecurity posture. The project's main goal was to protect against possible cyber-attacks and make sure that the aviation industry …

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.

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 …

Multifaceted Cybersecurity Analysis: Reconnaissance, Exploitation And Mitigation In A Controlled Network Environment, Austin Coontz

Williams Honors College, Honors Research Projects

This report details a network penetration test in a simulated environment using GNS3, focusing on the configuration of routers, switches, and hosts. The project successfully identified and exploited network vulnerabilities, including FTP access, misconfigured sudo permissions, and SMB protocol weaknesses. The penetration testing process utilized tools like fping and nmap for reconnaissance and vulnerability scanning, revealing the importance of device configurations in network security. The project concluded with mitigation strategies, emphasizing the need for secure access, robust password policies, and security controls. The experience underscored the significance of continuous learning and adaptation in the ever-evolving field of cybersecurity. The project …

Behavioral Biometrics-Based Continuous User Authentication, Sanket Vilas Salunke

Electronic Thesis and Dissertation Repository

The field of cybersecurity is exploring new ways to defend against cyber-attacks, including a technique called continuous user authentication. This method uses keystroke (typing) data to continuously match the user's typing pattern with patterns previously recorded using artificial intelligence (AI) to identify the user. While this approach has the potential to improve security, it also has some challenges, including the time it takes to register a user, the performance of machine learning algorithms on real-world data, and latency within the system. In this study, the researchers proposed solutions to these issues by using transfer learning to reduce user registration time, …

Cyber Resilience Analytics For Cyber-Physical Systems, Md Ariful Haque

Electrical & Computer Engineering Theses & Dissertations

Cyber-physical systems (CPSs) are complex systems that evolve from the integrations of components dealing with physical processes and real-time computations, along with networking. CPSs often incorporate approaches merging from different scientific fields such as embedded systems, control systems, operational technology, information technology systems (ITS), and cybernetics. Today critical infrastructures (CIs) (e.g., energy systems, electric grids, etc.) and other CPSs (e.g., manufacturing industries, autonomous transportation systems, etc.) are experiencing challenges in dealing with cyberattacks. Major cybersecurity concerns are rising around CPSs because of their ever-growing use of information technology based automation. Often the security concerns are limited to probability-based possible attack …

Software Protection And Secure Authentication For Autonomous Vehicular Cloud Computing, Muhammad Hataba

Dissertations

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC.

In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our …

Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia

Doctoral Dissertations and Master's Theses

Aviation cybersecurity research has proven to be a complex topic due to the intricate nature of the aviation ecosystem. Over the last two decades, research has been centered on isolated modules of the entire aviation systems, and it has lacked the state-of-the-art tools (e.g. ML/AI methods) that other cybersecurity disciplines have leveraged in their fields. Security research in aviation in the last two decades has mainly focused on: (i) reverse engineering avionics and software certification; (ii) communications due to the rising new technologies of Software Defined Radios (SDRs); (iii) networking cybersecurity concerns such as the inter and intra connections of …

Anonymization & Generation Of Network Packet Datasets Using Deep Learning, Spencer K. Vecile

Electronic Thesis and Dissertation Repository

Corporate networks are constantly bombarded by malicious actors trying to gain access. The current state of the art in protecting networks is deep learning-based intrusion detection systems (IDS). However, for an IDS to be effective it needs to be trained on a good dataset. The best datasets for training an IDS are real data captured from large corporate networks. Unfortunately, companies cannot release their network data due to privacy concerns creating a lack of public cybersecurity data. In this thesis I take a novel approach to network dataset anonymization using character-level LSTM models to learn the characteristics of a dataset; …

Exploring Artificial Intelligence (Ai) Techniques For Forecasting Network Traffic: Network Qos And Security Perspectives, Ibrahim Mohammed Sayem

Electronic Thesis and Dissertation Repository

This thesis identifies the research gaps in the field of network intrusion detection and network QoS prediction, and proposes novel solutions to address these challenges. Our first topic presents a novel network intrusion detection system using a stacking ensemble technique using UNSW-15 and CICIDS-2017 datasets. In contrast to earlier research, our proposed novel network intrusion detection techniques not only determine if the network traffic is benign or normal, but also reveal the type of assault in the flow. Our proposed stacking ensemble model provides a more effective detection capability than the existing works. Our proposed stacking ensemble technique can detect …

Cyber Deception For Critical Infrastructure Resiliency, Md Ali Reza Al Amin

Computational Modeling & Simulation Engineering Theses & Dissertations

The high connectivity of modern cyber networks and devices has brought many improvements to the functionality and efficiency of networked systems. Unfortunately, these benefits have come with many new entry points for attackers, making systems much more vulnerable to intrusions. Thus, it is critically important to protect cyber infrastructure against cyber attacks. The static nature of cyber infrastructure leads to adversaries performing reconnaissance activities and identifying potential threats. Threats related to software vulnerabilities can be mitigated upon discovering a vulnerability and-, developing and releasing a patch to remove the vulnerability. Unfortunately, the period between discovering a vulnerability and applying a …

Investigation Of Python Variable Privacy, Joshua Bartholomew

Honors Theses

This study looks at the relative security of Python regarding private variables and functions used in most other programming languages. Python has only grown in popularity due to its simple syntax and developing capabilities. However, little research has been published about how secure Python code and programs compiled from Python code actually are. This research seeks to expose vulnerabilities in Python code and determine what must be done for these vulnerabilities to be exploited by hackers to abuse potentially sensitive information contained within the program.

The proposed methodology includes examining the private variable concept in other programming languages and conducting …

Securing Infiniband Networks With End-Point Encryption, Noah B. Diamond

Theses and Dissertations

The NVIDIA-Mellanox Bluefield-2 is a 100 Gbps high-performance network interface which offers hardware offload and acceleration features that can operate directly on network traffic without routine involvement from the ARM CPU. This allows the ARM multi-core CPU to orchestrate the hardware to perform operations on both Ethernet and RDMA traffic at high rates rather than processing all the traffic directly. A testbed called TNAP was created for performance testing and a MiTM verification process called MiTMVMP is used to ensure proper network configuration. The hardware accelerators of the Bluefield-2 support a throughput of nearly 86 Gbps when using IPsec to …

A Trusted Platform For Unmanned Aerial Vehicle-Based Bridge Inspection Management System, Hwapyeong Song

Theses, Dissertations and Capstones

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for …

Few-Shot Malware Detection Using A Novel Adversarial Reprogramming Model, Ekula Praveen Kumar

Browse all Theses and Dissertations

The increasing sophistication of malware has made detecting and defending against new strains a major challenge for cybersecurity. One promising approach to this problem is using machine learning techniques that extract representative features and train classification models to detect malware in an early stage. However, training such machine learning-based malware detection models represents a significant challenge that requires a large number of high-quality labeled data samples while it is very costly to obtain them in real-world scenarios. In other words, training machine learning models for malware detection requires the capability to learn from only a few labeled examples. To address …

Examining Cooperative System Responses Against Grid Integrity Attacks, Alexander D. Parady

Honors Undergraduate Theses

Smart grid technologies are integral to society’s transition to sustainable energy sources, but they do not come without a cost. As the energy sector shifts away from a century’s reliance on fossil fuels and centralized generation, technology that actively monitors and controls every aspect of the power infrastructure has been widely adopted, resulting in a plethora of new vulnerabilities that have already wreaked havoc on critical infrastructure. Integrity attacks that feedback false data through industrial control systems, which result in possible catastrophic overcorrections and ensuing failures, have plagued grid infrastructure over the past several years. This threat is now at …

Federated Agentless Detection Of Endpoints Using Behavioral And Characteristic Modeling, Hansaka Angel Dias Edirisinghe Kodituwakku

Doctoral Dissertations

During the past two decades computer networks and security have evolved that, even though we use the same TCP/IP stack, network traffic behaviors and security needs have significantly changed. To secure modern computer networks, complete and accurate data must be gathered in a structured manner pertaining to the network and endpoint behavior. Security operations teams struggle to keep up with the ever-increasing number of devices and network attacks daily. Often the security aspect of networks gets managed reactively instead of providing proactive protection. Data collected at the backbone are becoming inadequate during security incidents. Incident response teams require data that …

Addressing Security And Privacy Issues By Analyzing Vulnerabilities In Iot Applications, Francsico Javier Candelario Burgoa

Open Access Theses & Dissertations

The Internet of Things (IoT) environment has been expanding rapidly for the past few years into several areas of our lives, from factories, to stores and even into our own homes. All these new devices in our homes make our day-to-day lives easier and more comfortable with less effort on our part, converting our simple houses into smart homes. This increase in inter-connectivity brings multiple benefits including the improvement in energy efficiency in our homes, however it also brings with it some potential dangers since more points of connection mean more potential vulnerabilities in our grid. These vulnerabilities bring security …

Towards Verifying Smartphone Users Via Gripping Hand Image Classification, Kaitlyn M. Madden

LSU Master's Theses

Smartphones continue to proliferate throughout our daily lives, not only in sheer quantity but also their ever-growing list of uses. They are no longer just for communication and the occasional phone game. Smartphones can be used to open garage doors, transfer money, see who is at your front door, and much, much more. With this increased dependence and use, smartphone security is critical. In this paper we propose a system to verify a user’s identity by applying a convolutional neural network (CNN) model to an image of the user’s hand while holding their device. This model aims to address situations …

Real-Time Machine Learning For Quickest Detection, Yongxin Liu

Doctoral Dissertations and Master's Theses

Safety-critical Cyber-Physical Systems (CPS) require real-time machine learning for control and decision making. One promising solution is to use deep learning to discover useful patterns for event detection from heterogeneous data. However, deep learning algorithms encounter challenges in CPS with assurability requirements: 1) Decision explainability, 2) Real-time and quickest event detection, and 3) Time-eficient incremental learning.

To address these obstacles, I developed a real-time Machine Learning Framework for Quickest Detection (MLQD). To be specific, I first propose the zero-bias neural network, which removes decision bias and preferabilities from regular neural networks and provides an interpretable decision process. Second, I discover …