Review of the malware categorization in the era of changing cybethreats landscape: Common approaches, challenges and future needs

Andrii Shalaginov, Geir Olav Dyrkolbotn, Mamoun Alazab

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    5 Citations (Scopus)

    Abstract

    Malicious software threats have been known to Information Security professionals for over several decades since the dawn of computers. Developers of such software have been keeping up with technologies addressing known and unknown vulnerabilities for successful infection. With the growing amount of devices connected to the Internet, it has become apparent that the categorization of millions of malware samples is an emerging challenge. Malware labelling has become a significant challenge in the light of a large number of malware samples appearing daily. Many researchers and anti-virus vendors developed their unique naming methods that do not contribute to efficient incident response and remediation of the malware infections on a global scale. In this paper, first, we provide a view on the modern approaches to malware categorization concerning the needs of malware detection and analysis, specifically focusing on general modus operandi and automated analysis. Then, we review the State of the Art technical reports from the antivirus on the existing labelling initiatives and their usage by vendors. Finally, we give practical insight into future needs and current challenges of the naming schemes using ground truth knowledge. This review aims at bridging a knowledge gap between the existing labelling approaches, threats and malware functionality and problems related to large-scale malware classification.

    Original languageEnglish
    Title of host publicationMalware Analysis Using Artificial Intelligence and Deep Learning
    EditorsMark Stamp, Mamoun Alazab, Andrii Shalaginov
    PublisherSpringer
    Pages71-96
    Number of pages26
    ISBN (Electronic)9783030625825
    ISBN (Print)9783030625818
    DOIs
    Publication statusPublished - 20 Dec 2020

    Bibliographical note

    Publisher Copyright:
    © The Author(s), 2021. All rights reserved.

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