Problem-Solving
Overview
Problem-solving is an important skill I have developed through my cybersecurity coursework and professional experiences. Cybersecurity often requires identifying a problem, analyzing information, considering possible solutions, and determining the best way to address an issue. Through hands-on projects, technical assignments, and challenging coursework, I have learned to approach problems carefully and use critical thinking to find effective solutions.
Artifact 1: Zeek Intrusion Detection Paper
What it is:
A research paper examining whether Zeek-based network intrusion detection systems can be deployed while protecting student privacy rights.
What I did:
I researched how Zeek can be used to monitor network activity and examined the privacy concerns that can come with network monitoring. I considered both the cybersecurity benefits and the potential privacy risks before developing my conclusion.
What it demonstrates:
This artifact demonstrates my ability to analyze a complex problem, research different perspectives, evaluate potential risks, and develop a solution based on evidence. It also shows my ability to connect cybersecurity technology with privacy and ethical considerations.
Artifact 2: Gradient Boosting Intrusion Detection Project
What it is:
A machine-learning project focused on using Gradient Boosting to identify potential network intrusions.
What I did:
I worked with an intrusion-detection dataset and used Python and Scikit-learn to prepare the data and develop a Gradient Boosting model. I also worked with hyperparameter tuning to improve the model’s performance and determine an effective approach for detecting suspicious network activity.
What it demonstrates:
This artifact demonstrates my ability to analyze a cybersecurity problem, work with data, test different approaches, and improve a solution based on the results. It also shows my ability to apply machine-learning techniques to a real-world cybersecurity problem.
Artifact 3: K-means/DBSCAN Anomaly Detection Project
What it is:
A cybersecurity data analysis project that used K-Means and DBSCAN clustering techniques to identify patterns and potential anomalies in a dataset.
What I did:
I worked with the dataset and applied K-Means and DBSCAN to analyze the data and identify unusual patterns. I compared the approaches and examined the results to better understand how clustering can be used for anomaly detection.
What it demonstrates:
This artifact demonstrates my ability to break down a cybersecurity problem, analyze data, test different approaches, and evaluate the results. It also shows my ability to use critical thinking when determining how different techniques can be applied to identify potential security issues.
