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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…

For instructive purposes, we produce a toy dataset representing the percentage of each type of malware in time (Step 1). With a larger amount of historical data, such a dataset can indicate where to channel your resources in the domain of security. We collect the data in one place and produce visualization plots (Step 2). We would like to perform simple forecasting, so we import ARMA, which stands for autoregressive–moving-average model, and is a generalization of the moving-average model. For simplicity, we specialize ARMA to moving average (MA). In Step 4, we employ MA to make a prediction on how the percentages of malware will evolve to the next time period. With a larger dataset, it is prudent to attempt different models, ...

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Publisher Resources

ISBN: 9781789614671Supplemental Content