Machine learning plays a role in a wide variety of fields. It can be used for predicting stock prices, identifying diseases, and even teaching Mario how to avoid mushrooms. This project explores the use of machine learning in realm of threat intelligence. There are many sources for professionals to keep up to date on the latest threats to software (NVD, PacketStorm, Twitter, etc.). However, it can become over cumbersome for individuals to monitor all of these sources manually. Building an automated string match system is a good first step to tackle this problem, but many false positives may be returned. A good way to limit this issue is to use machine learning and train a classifier to identify what information is relevant and what is irrelevant. This paper explores 3 different algorithms for building a text classifier and conducts tests to see which is the most accurate at identifying threats.
Vangore, Jacob, "Machine Learning and Threat Intelligence" (2018). Student Scholarship - Computer Science. 3.
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