Raghad Alharbi

Cybersecurity Specialization · Cohort 2025

Leveraging Machine Learning for Security Operations

This project focuses on exploring machine learning (ML) techniques to enhance the efficiency of the Security Operations Center (SOC). By automating lower-level alert triaging, the goal is to save time and reallocate resources to higher-value tasks. Students will design and build tools that leverage ML for data preprocessing, feature optimization, and advanced alert analysis. The project will also include developing pipelines and user interfaces to deliver a production-ready solution. This project aims to provide students with experience in cutting-edge security and ML applications while delivering a practical tool to enhance SOC operations. The resulting solution will improve alert accuracy and streamline investigation workflows, showcasing the transformative potential of ML in cybersecurity.

Mentor: Jeremy Bandini

See it in the program report (PDF)

Cybersecurity Specialization · Cohort 2024

InternalEYE: Insider Threat Detection Using Machine Learning

Read the final report (PDF)