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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 start this recipe by creating a large dataset of LSB steganography container images using the software known as Aletheia (step 1). Aletheia offers a wide array of functionality. Run the following command with no arguments:

$ ./aletheia.py

The preceding command prints out the following information about aletheia:

./aletheia.py <command>COMMANDS:Attacks to LSB replacement:- spa: Sample Pairs Analysis.- rs: RS attack.ML-based detectors:- esvm-predict: Predict using eSVM.- e4s-predict: Predict using EC.Feature extractors:- srm: Full Spatial Rich Models.- hill-maxsrm: Selection-Channel-Aware Spatial Rich Models for HILL.- srmq1: Spatial Rich Models with fixed quantization q=1c.- scrmq1: Spatial Color Rich Models with fixed quantization ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content