Malicious URL Detection

• Course: CMPT733 Big Data Lab 2 (SFU)
• Tech Stack: Google Colab, Python (pandas, matplotlib, seaborn, scikit-learn), AWS Services, Flask, HTML, CSS, JS)
• Article: Link to Medium Article/Blog Post
• Github: Link to Project Repository

• Attained an effective way to detect malicious URLs, that comprise 60% of all cyber-attacks
• Extracted extensive features to gain a rich dataset and executed the entire data science pipeline
• Visualized to gain insights about features and trained XGBoost model, that attained an accuracy of 95%
• Assembled an interactive interface and a chrome extension as the end product for users