Graduation Year
2017
Date of Submission
4-2017
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Computer Science
Reader 1
Mariam Salloum
Terms of Use & License Information
Rights Information
© 2017 Aidan J Cheng
Abstract
There is a need for better predictive model that reduces the number of malicious URLs being sent through emails. This system should learn from existing metadata about URLs. The ideal solution for this problem would be able to learn from its predictions. For example, if it predicts a URL to be malicious, and that URL is deemed safe by the sandboxing environment, the predictor should refine its model to account for this data. The problem, then, is to construct a model with these characteristics that can make these predictions for the vast number of URLs being processed. Given that the current system does not employ machine learning methods, we intend to investigate multiple such models and summarize which of those might be worth pursuing on a large scale.
Recommended Citation
Cheng, Aidan, "Using Machine Learning to Detect Malicious URLs" (2017). CMC Senior Theses. 1567.
https://scholarship.claremont.edu/cmc_theses/1567
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.
