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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

How it works…

We begin this recipe by loading in a previously featurized dataset and specifying a desired FPR constraint of 1% (step 1). The value to be used in practice depends highly on the situation and type of file being considered. There are a few considerations to follow: if the file is extremely common, but rarely malicious, such as a PDF, the desired FPR will have to be set very low, for example, 0.01%.

If the system is supported by additional systems that will double-check its verdict without human effort, then a high FPR might not be detrimental. Finally, a customer may have a preference, which will suggest a recommended value. We define a pair of convenience functions for FPR and TPR in step 2—these functions are very handy and ...

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Publisher Resources

ISBN: 9781789614671Supplemental Content