Cybersecurity
Credential Theft & Identity Based Attacks
An in-depth analysis of modern credential theft vectors including phishing, MFA fatigue, infostealer malware, and session hijacking — with coverage of Zero Trust and phishing-resistant defenses.
Cybersecurity Vulnerability Risk Tracker (VRT)
A full database-backed system for tracking and scoring cybersecurity vulnerabilities, designed in ISE 305: Database Design and Practice. Combines relational data modeling with security domain knowledge.
Data Analytics & Statistics
One Predictor Linear Regression Analysis
OLS regression analysis on a 630-observation dataset using R. Includes missing data imputation via the MICE bootstrap method, ANOVA table generation, scatter plot visualization, and 95%/99% confidence intervals for the slope.
Project 2: Data Analysis - Multiple Regression
R-based statistics project analyzing environmental and genetic variables using multiple regression, Box-Cox transformation, stepwise model selection, residual plots, adjusted R-squared, BIC, and ANOVA results.
Database Design
Cybersecurity Vulnerability Risk Tracker (VRT)
Designed a relational database system for tracking cybersecurity vulnerabilities, affected systems, patching progress, team assignments, and risk scores using MS Access and SQL queries.
ISE 305 Tables RDM
Documented the relational table structures, primary keys, foreign keys, field types, and implemented MS Access relationships for the vulnerability risk tracker database.
ISE 305 Final Project RDM
Created the final relational data model and Access form documentation, including systems, vulnerabilities, patches, teams, assignments, and parent-child form relationships.
