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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

Malicious URL detector

Malicious URLs cause billions of dollars of damage every year by hosting spam, malware, and exploits, as well as stealing information. Traditionally, defenses against these have relied on blacklists and whitelists – lists of URLs that are considered malicious, and lists of URLs that are considered safe. However, blacklists suffer from a lack of generality and an inability to defend against previously unseen malicious URLs. To remedy the situation, machine learning techniques have been developed. In this recipe, we'll run a malicious URL detector using character-level recurrent neural networks with Keras. The code is based on https://github.com/chen0040/keras-malicious-url-detector.

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Publisher Resources

ISBN: 9781789614671Supplemental Content