Abstract
With rapidly evolving threat landscape surrounding malware, intelligent defenses based on machine learning are paramount. In this chapter, we review the literature proposed in the past decade and identify the state-of-the-art in various related research directions—malware detection, malware analysis, adversarial malware, and malware author attribution. We discuss challenges that emerge when machine learning is applied to malware. We also identify the key issues that need to be addressed by the research community in order to further deepen and systematize research in the malware domain.
Original language | English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Publisher | Springer |
Chapter | 10 |
Pages | 217-253 |
Number of pages | 37 |
ISBN (Electronic) | 978-3-030-98795-4 |
ISBN (Print) | 978-3-030-98794-7 |
DOIs | |
Publication status | Published - 2022 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13049 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.