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Protecting from Malware Obfuscation Attacks through Adversarial Risk Analysis

Cryptography and Security 2019-11-12 v1 Machine Learning Machine Learning

Abstract

Malware constitutes a major global risk affecting millions of users each year. Standard algorithms in detection systems perform insufficiently when dealing with malware passed through obfuscation tools. We illustrate this studying in detail an open source metamorphic software, making use of a hybrid framework to obtain the relevant features from binaries. We then provide an improved alternative solution based on adversarial risk analysis which we illustrate describe with an example.

Keywords

Cite

@article{arxiv.1911.03653,
  title  = {Protecting from Malware Obfuscation Attacks through Adversarial Risk Analysis},
  author = {Alberto Redondo and David Rios Insua},
  journal= {arXiv preprint arXiv:1911.03653},
  year   = {2019}
}
R2 v1 2026-06-23T12:10:09.372Z