Intelligent Malware Defenses

Book chapter (2022)

Authors

A. Nadeem Cyber Security - EEMCS
Vera Rimmer imec-DistriNet, KU Leuven
Joosen Wouter imec-DistriNet, KU Leuven
S.E. Verwer Cyber Security - EEMCS
Research Group
Cyber Security (EEMCS) (TU Delft)
Copyright: © 2022 A. Nadeem, Vera Rimmer, Joosen Wouter, S.E. Verwer
DOI: https://doi.org/10.1007/978-3-030-98795-4_10
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Cyber Security

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.