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Articles 1 - 5 of 5
Full-Text Articles in Cybersecurity
Video Game Hacking, A General Problem With Generalized Solutions, Luke Rowe
Video Game Hacking, A General Problem With Generalized Solutions, Luke Rowe
Master's Theses
As video games continue to get more popular and lucrative, the number of malicious actors seeking to exploit them grows with it. As this industry expands, so does the importance of securing games against cheating and abuse. This thesis aims to educate developers to help mitigate the abuse of video games by these malicious actors. The goal of this thesis is to provide a foundational framework for thinking like a hacker and how to make games harder to abuse once a hacker bypasses conventional anti-cheat software.
This thesis outlines some of the most common cheating methods and provides general context …
Exploiting Compiler-Introduced Vulnerabilities In C: A Cross-Compiler And Cross-Architecture Analysis Of Undefined Behavior, Erik Mccutchen
Exploiting Compiler-Introduced Vulnerabilities In C: A Cross-Compiler And Cross-Architecture Analysis Of Undefined Behavior, Erik Mccutchen
Master's Theses
Compilers are a critical component in generating secure software across engineering disciplines. However, languages like C that permit undefined behavior introduce a fundamental tension between the compiler’s interpretation of undefined behavior and the security of the generated code. This tension can result in security vulnerabilities that, from the programmer's perspective, are ``created'' by the compiler. The widespread use of these languages, combined with the complexity of modern optimizations and limited developer visibility into compiler behavior, makes these vulnerabilities both pervasive and difficult to detect.
Building on prior work, this thesis refines a dataset of C code snippets that exhibit Compiler-Introduced …
Spos: An Attestation Solution For The Detection And Mitigation Of Point Of Sale Malware, Damian Singh Dhesi
Spos: An Attestation Solution For The Detection And Mitigation Of Point Of Sale Malware, Damian Singh Dhesi
Master's Theses
Securing 95% of card present transactions, accounting for billions of transactions a year, has made EMV the premier protocol for card-based payment. Created by and named after Europay, Mastercard, and Visa, the EMV protocol provides multiple solutions to resolve security concerns with the outdated, swipe-based, magnetic stripe payment. Such solutions are Chip and PIN which provides a more secure transaction at a significant time cost and EMV contactless which provides improved security to Chip and PIN at greater ease of use with its quick, tap-to-pay based payment. However, regardless of how secure the EMV protocol makes the card side of …
Efficient Gan-Based Adversarial Example Generation Against Ml-Based Network Intrusion Detection Systems, Darren D. Hartono
Efficient Gan-Based Adversarial Example Generation Against Ml-Based Network Intrusion Detection Systems, Darren D. Hartono
Master's Theses
In the realm of network security, Network Intrusion Detection Systems (NIDS) are essential for identifying and mitigating malicious activities targeting networked devices. Traditionally, these systems have relied on signature-based and anomaly-based detection techniques. However, the increasing complexity and adapt- ability of cyber threats have driven the adoption of Machine Learning (ML) ap- proaches in modern NIDS, significantly improving their ability to detect a wider range of attack vectors. Despite these advancements, ML-based NIDS remain vulnerable to adversarial examples—deliberately crafted inputs designed to mislead models and trigger incorrect classifications. Originally identified in the field of computer vision, adversarial examples now pose …
Real-Time Network Simulations For Ml/Dl Ddos Detection Using Docker, Luis D. Garcia
Real-Time Network Simulations For Ml/Dl Ddos Detection Using Docker, Luis D. Garcia
Master's Theses
As the integration of artificial intelligence (AI) within cybersecurity continues to
grow, machine learning (ML) and deep learning (DL) models are increasingly used to
detect cyber attacks. However, these models are rarely evaluated in real-time attack
scenarios to see how subtle changes from the real networking environment can affect
their predictions. To address this issue, we propose a scalable, platform-independent
Docker testbed specifically designed for simulating real-time Distributed Denial of
Service (DDoS) attack scenarios that allows researchers to deploy and evaluate their
pre-trained, ML and DL detection models. Our framework is simple to configure
and can run across Intel and …