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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

Neural network-assisted fuzzing

Fuzzing is a software vulnerability detection method wherein a large number of random inputs are fed into a program in search of ones that will cause a crash, unwanted information leak, or other unintended behavior. In automated fuzzing, a program generates these inputs. Generally, automated fuzzers suffer from the shortcoming that they tend to get stuck trying redundant inputs. For this reason, AI-based fuzzers have recently been developed. In this recipe, we'll employ NEUZZ, a neural network-based fuzzer by She et al. (see https://arxiv.org/abs/1807.05620), to find unknown vulnerabilities in software.

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Publisher Resources

ISBN: 9781789614671Supplemental Content