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PyAntiPhish: A Python-Based Machine Learning Detector of Phishing Websites and An Examination of Relevant URL-Based Features

Description
Phishing is one of most common and effective attack vectors in modern cybercrime. Rather than targeting a technical vulnerability in a computer system, phishing attacks target human behavioral or emotional tendencies through manipulative emails, text messages, or phone calls. Through PyAntiPhish, I attempt to create my own version of an…

Phishing is one of most common and effective attack vectors in modern cybercrime. Rather than targeting a technical vulnerability in a computer system, phishing attacks target human behavioral or emotional tendencies through manipulative emails, text messages, or phone calls. Through PyAntiPhish, I attempt to create my own version of an anti-phishing solution, through a series of experiments testing different machine learning classifiers and URL features. With an end-goal implementation as a Chromium browser extension utilizing Python-based machine learning classifiers (those available via the scikit-learn library), my project uses a combination of Python, TypeScript, Node.js, as well as AWS Lambda and API Gateway to act as a solution capable of blocking phishing attacks from the web browser.
ContributorsYang, Branden (Author) / Osburn, Steven (Thesis director) / Malpe, Adwith (Committee member) / Ahn, Gail-Joon (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05

Plexify: A New Way to Perform Circuit Simplification

Description
For my thesis, I designed a program called Plexify that would take in truth tables as CSV files and be able to generate the minimized sum of products or product of sums expression for any of the output variables in the truth table. My program can run on any Windows…

For my thesis, I designed a program called Plexify that would take in truth tables as CSV files and be able to generate the minimized sum of products or product of sums expression for any of the output variables in the truth table. My program can run on any Windows device and the repository for the program can be found at https://github.com/RockPalmer/Plexify.
ContributorsPalmer, Rock (Author) / Osburn, Steven (Thesis director) / Platt, Dane (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2024-05