No Need to Teach New Tricks to Old Malware: Winning an Evasion Challenge with XOR-based Adversarial Samples-Reference-Cited by-同舟云学术

No Need to Teach New Tricks to Old Malware: Winning an Evasion Challenge with XOR-based Adversarial Samples

Published:2020-11-19 Issue: Volume: Page:
ISSN:
Container-title:Reversing and Offensive-oriented Trends Symposium
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Author:

Ceschin Fabricio¹,Botacin Marcus¹,Lüders Gabriel¹,Gomes Heitor Murilo²,Oliveira Luiz¹,Gregio Andre¹

Affiliation:

1. Federal University of Paraná, Brazil

2. University of Waikato, New Zealand

Funder

Brazilian National Counsel of Technological and Scientific Development

Coordination for the Improvement of Higher Education Personnel

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3433667.3433669

Reference49 articles.

1. Hyrum Anderson. 2019. Machine Learning Static Evasion Competition. https://www.elastic.co/pt/blog/machine-learning-static-evasion-competition/. Hyrum Anderson. 2019. Machine Learning Static Evasion Competition. https://www.elastic.co/pt/blog/machine-learning-static-evasion-competition/.

2. Manuel Baena-Garćıa José del Campo-Ávila Raúl Fidalgo Albert Bifet Ricard Gavaldà and Rafael Morales-Bueno. 2006. Early Drift Detection Method. Manuel Baena-Garćıa José del Campo-Ávila Raúl Fidalgo Albert Bifet Ricard Gavaldà and Rafael Morales-Bueno. 2006. Early Drift Detection Method.

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