Information Security Commons^™

Alpha Phi-Shing Fraternity: Phishing Assessment In A Higher Education Institution, Marco Casagrande, Mauro Conti, Monica Fedeli, Eleonora Losiouk

Journal of Cybersecurity Education, Research and Practice

Phishing is a common social engineering attack aimed to steal personal information. Universities attract phishing attacks because: 1) they store employees and students sensitive data, 2) they save confidential documents, 3) their infrastructures often lack security. In this paper, we showcase a phishing assessment at the University of Redacted aimed to identify the people, and the features of such people, that are more susceptible to phishing attacks. We delivered phishing emails to 1.508 subjects in three separate batches, collecting a clickrate equal to 30%, 11% and 13%, respectively. We considered several features (i.e., age, gender, role, working/studying field, email template) …

Finding Forensic Evidence In The Operating System's Graphical User Interface, Edward X. Wilson Mr.

LSU Master's Theses

A branch of cyber security known as memory forensics focuses on extracting meaningful evidence from system memory. This analysis is often referred to as volatile memory analysis, and is generally performed on memory captures acquired from target systems. Inside of a memory capture is the complete state of a system under investigation, including the contents of currently running as well as previously executed applications. Analysis of this data can reveal a significant amount of activity that occurred on a system since the last reboot. For this research, the Windows operating system is targeted. In particular, the graphical user interface component …

Unmasking Deception In Vanets: A Decentralized Approach To Verifying Truth In Motion, Susan Zehra, Syed R. Rizvi, Steven Olariu

College of Sciences Posters

VANET, which stands for "Vehicular Ad Hoc Network," is a wireless network that allows vehicles to communicate with each other and with infrastructure, such as Roadside Units (RSUs), with the aim of enhancing road safety and improving the overall driving experience through real-time exchange of information and data. VANET has various applications, including traffic management, road safety alerts, and navigation. However, the security of VANET can be compromised if a malicious user alters the content of messages transmitted, which can harm both individual vehicles and the overall trust in VANET technology. Ensuring the correctness of messages is crucial for the …

A Systematic Review Of Cryptocurrencies Use In Cybercrimes, Kieran B D Human

Graduate Thesis and Dissertation 2023-2024

Cryptocurrencies are one of the most prominent applications of blockchain systems. While cryptocurrencies promise many features and advantages, such as decentralization, anonymity, and ease of access, those very features can be abused. For instance, as documented in various recent works, cryptocurrencies have been frequently abused in many different forms of cybercrime. Despite the plethora of works on measuring and understanding the abuse of cryptocurrencies in the digital space, there has been no work on systemizing this knowledge by comprehensively understanding those contributions, contrasting them based on their merit, and understanding the gap in this research space.

This thesis initiates the …

Towards A Holistic And Comparative Analysis Of The Free Content Web: Security, Privacy, And Performance, Abdulrahman Alabduljabbar

Electronic Theses and Dissertations, 2020-2023

Free content websites that provide free books, music, games, movies, etc., have existed on the Internet for many years. While it is a common belief that such websites might be different from premium websites providing the same content types in terms of their security, a rigorous analysis that supports this belief is lacking from the literature. In particular, it is unclear if those websites are as safe as their premium counterparts. In this dissertation, we set out to investigate the similarities and differences between free content and premium websites, including their risk profiles. Moreover, we analyze and quantify through measurements …

Unlocking User Identity: A Study On Mouse Dynamics In Dual Gaming Environments For Continuous Authentication, Marcho Setiawan Handoko

All Graduate Theses, Dissertations, and Other Capstone Projects

With the surge in information management technology reliance and the looming presence of cyber threats, user authentication has become paramount in computer security. Traditional static or one-time authentication has its limitations, prompting the emergence of continuous authentication as a frontline approach for enhanced security. Continuous authentication taps into behavior-based metrics for ongoing user identity validation, predominantly utilizing machine learning techniques to continually model user behaviors. This study elucidates the potential of mouse movement dynamics as a key metric for continuous authentication. By examining mouse movement patterns across two contrasting gaming scenarios - the high-intensity "Team Fortress" and the low-intensity strategic …

Applying Machine Learning To Categorize Distinct Categories Of Network Traffic, Isaac M. Dunham

Senior Honors Theses and Projects

The recent rapid growth of the field of data science has made available to all fields opportunities to leverage machine learning. Computer network traffic classification has traditionally been performed using static, pre-written rules that are easily made ineffective if changes, legitimate or not, are made to the applications or protocols underlying a particular category of network traffic. This paper explores the problem of network traffic classification and analyzes the viability of having the process performed using a multitude of classical machine learning techniques against significant statistical similarities between classes of network traffic as opposed to traditional static traffic identifiers.

To …

Discovering Vulnerabilities And Designing Trustworthy Defenses In Iot Systems And Devices, Bryan Pearson

Electronic Theses and Dissertations, 2020-2023

Internet of Things (IoT) dominates many functions in the modern world, from sensing and reporting temperature, humidity, and air quality, to controlling and automating homes, commercial buildings, and equipment. However, IoT systems have received scrutiny in recent years due to countless security incidents, which can have physical and even deadly consequences. This research provides a comprehensive assessment of the security of IoT systems and devices, including low-cost microcontroller (MCU) based sensors, cloud services, and Building Automation Systems (BAS). We begin by exploring the current landscape of vulnerabilities and defenses in modern IoT applications. We show that many security needs can …

Enabling Dapps Data Exchange With Hardware-Assisted Secure Oracle Network, Yue Li

Theses and Dissertations--Computer Science

Decentralized applications (dApps), enabled by the blockchain and smart contract technology, are known for allowing distrustful parties to execute business logic without relying on a central authority. Compared to regular applications, dApps offer a wide range of benefits, including security by design, trustless transactions, and resistance to censorship. However, dApps need to access real-world data to achieve their full potential, relying on the data oracles. Oracles act as bridges between blockchains and the outside world, providing essential data to the smart contracts that power dApps. A significant challenge in integrating oracles into the dApp ecosystem is the Oracle Problem …

An Empirical Assessment Of The Use Of Password Workarounds And The Cybersecurity Risk Of Data Breaches, Michael Joseph Rooney

CCAC Theses and Dissertations

Passwords have been used for a long time to grant controlled access to classified spaces, electronics, networks, and more. However, the dramatic increase in user accounts over the past few decades has exposed the realization that technological measures alone cannot ensure a high level of IS security; this leaves the end-users holding a critical role in protecting their organization and personal information. The increased use of IS as a working tool for employees increases the number of accounts and passwords required. Despite being more aware of password entropy, users still often participate in deviant password behaviors, known as ‘password workarounds’ …

Defending Ai-Based Automatic Modulation Recognition Models Against Adversarial Attacks, Haolin Tang, Ferhat Ozgur Catak, Murat Kuzlu, Evren Catak, Yanxiao Zhao

Engineering Technology Faculty Publications

Automatic Modulation Recognition (AMR) is one of the critical steps in the signal processing chain of wireless networks, which can significantly improve communication performance. AMR detects the modulation scheme of the received signal without any prior information. Recently, many Artificial Intelligence (AI) based AMR methods have been proposed, inspired by the considerable progress of AI methods in various fields. On the one hand, AI-based AMR methods can outperform traditional methods in terms of accuracy and efficiency. On the other hand, they are susceptible to new types of cyberattacks, such as model poisoning or adversarial attacks. This paper explores the vulnerabilities …

A Secure Emr Sharing System With Tamper Resistance And Expressive Access Control, Shengmin Xu, Jianting Ning, Yingjiu Li, Yinghui Zhang, Guowen Xu, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

To reduce the cost of human and material resources and improve the collaborations among medical systems, research laboratories and insurance companies for healthcare researches and commercial activities, electronic medical records (EMRs) have been proposed to shift from paperwork to friendly shareable electronic records. To take advantage of EMRs efficiently and reduce the cost of local storage, EMRs are usually outsourced to the remote cloud for sharing medical data with authorized users. However, cloud service providers are untrustworthy. In this paper, we propose an efficient, secure, and flexible EMR sharing system by introducing a novel cryptosystem called dual-policy revocable attribute-based encryption …

Intelligent Adaptive Gossip-Based Broadcast Protocol For Uav-Mec Using Multi-Agent Deep Reinforcement Learning, Zen Ren, Xinghua Li, Yinbin Miao, Zhuowen Li, Zihao Wang, Mengyao Zhu, Ximeng Liu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

UAV-assisted mobile edge computing (UAV-MEC) has been proposed to offer computing resources for smart devices and user equipment. UAV cluster aided MEC rather than one UAV-aided MEC as edge pool is the newest edge computing architecture. Unfortunately, the data packet exchange during edge computing within the UAV cluster hasn't received enough attention. UAVs need to collaborate for the wide implementation of MEC, relying on the gossip-based broadcast protocol. However, gossip has the problem of long propagation delay, where the forwarding probability and neighbors are two factors that are difficult to balance. The existing works improve gossip from only one factor, …

Explainable Ai For Android Malware Detection, Maithili Kulkarni

Master's Projects

Android malware detection based on machine learning (ML) is widely used by the mobile device security community. Machine learning models offer benefits in terms of detection accuracy and efficiency, but it is often difficult to understand how such models make decisions. As a result, popular malware detection strategies remain black box models, which may result in a lack of accountability and trust in the decisions made. The field of explainable artificial intelligence (XAI) attempts to shed light on such black box models. In this research, we apply XAI techniques to ML-based Android malware detection systems. We train classic ML models …

Spartanscript: New Language Design For Smart Contracts, Ajinkya Lakade

Master's Projects

Smart contracts have become a crucial element for developing decentralized applications on blockchain, resulting in numerous innovative projects on blockchain networks. Ethereum has played a significant role in this space by providing a high-performance Ethereum virtual machine, enabling the creation of several high- level programming languages that can run on the Ethereum blockchain. Despite its usefulness, the Ethereum Virtual Machine has been prone to security vulnerabilities that can result in developers succumbing to common pitfalls which are otherwise safeguarded by modern virtual machines used in programming languages. The project aims to introduce a new interpreted scripting programming language that closely …

Nft Artifact Prediction Using Machine Learning, Rishabh Pandey

Master's Projects

NFT Prediction Systems are web applications that provide their users with valuable insights about the artifact. These insights are useful for investors and collectors to make better decisions about their purchases. This project builds upon the same concept of prediction by developing a web application to dynamically provide recommendations based on user input and training an ML model to predict their cost. Preliminary work for the prediction system involved data collection, pre-processing, analysis, and filtering of large datasets from diverse sources. The project focused on the development of a user- friendly UI to enable seamless categorization of search results generated …

Spartan Price Oracle: A Schelling-Point Based Decentralized Pirce Oracle, Sihan He

Master's Projects

Nakamoto’s Bitcoin is the first decentralized digital cash system that utilizes a blockchain to manage transactions in its peer-to-peer network. The newer generation of blockchain systems, including Ethereum, extend their capabilities to support deployment of smart contracts within their peer-to-peer networks. However, smart contracts cannot acquire data from sources outside the blockchain since the blockchain network is isolated from the outside world. To obtain data from external sources, smart contracts must rely on Oracles, which are agents that bring data from the outside world to a blockchain network. However, guaranteeing that the oracle’s off-chain nodes are trustworthy remains a challenge. …

Ml-Based User Authentication Through Mouse Dynamics, Sai Kiran Davuluri

Master's Projects

Increasing reliance on digital services and the limitations of traditional authentication methods have necessitated the development of more advanced and secure user authentication methods. For user authentication and intrusion detection, mouse dynamics, a form of behavioral biometrics, offers a promising and non-invasive method. This paper presents a comprehensive study on ML-Based User Authentication Through Mouse Dynamics.

This project proposes a novel framework integrating sophisticated techniques such as embeddings extraction using Transformer models with cutting-edge machine learning algorithms such as Recurrent Neural Networks (RNN). The project aims to accurately identify users based on their distinct mouse behavior and detect unauthorized access …

Insecure Deserialization Detection In Python, Aneesh Verma

Master's Projects

The importance of Cyber Security is increasing every single day. From the emergence of new ransomware to major data breaches, the online world is getting dangerous. A multinational non- profit group devoted to online application security is called OWASP, or the Open Web Application Security Project. The OWASP Top 10 is a frequently updated report that highlights the ten most important vulnerabilities to web application security. Among these 10 vulnerabilities, there exists a vulnerability called Software and Data Integrity Failures. A subset of this vulnerability is Insecure Deserialization. An object is transformed into a stream of bytes through the serialization …

Steganographic Capacity Of Selected Machine Learning And Deep Learning Models, Lei Zhang

Master's Projects

As machine learning and deep learning models become ubiquitous, it is inevitable that there will be attempts to exploit such models in various attack scenarios. For example, in a steganographic based attack, information would be hidden in a learning model, which might then be used to gain unauthorized access to a computer, or for other malicious purposes. In this research, we determine the steganographic capacity of various classic machine learning and deep learning models. Specifically, we determine the number of low-order bits of the trained parameters of a given model that can be altered without significantly affecting the performance of …