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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

Anomaly detection with Isolation Forest

Anomaly detection is the identification of events in a dataset that do not conform to the expected pattern. In applications, these events may be of critical importance. For instance, they may be occurrences of a network intrusion or of fraud. We will utilize Isolation Forest to detect such anomalies. Isolation Forest relies on the observation that it is easy to isolate an outlier, while more difficult to describe a normal data point.

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Publisher Resources

ISBN: 9781789614671Supplemental Content