The rapid evolution of technology in the past years largely contributed to the digital transformation, however, attackers took advantage of it to spread malicious software (malware). Nowadays, malware has become more sophisticated, which makes it harder to be detected with traditional techniques. Over the years, attacks became, not only limited to computer-based operating systems, but also to that of mobilebased, which makes it even harder for analysts. Furthermore, this increases the need for more research in this direction. The technological evolution also gives researchers the chance to utilize Artificial Intelligence widely and leverage its capabilities in many fields in general and in the field of malware detection in particular. This paper provides a literature review on malware detection using Artificial Intelligence techniques and specifically, Machine Learning and Deep Learning techniques. The paper helps researchers to have a broad idea of the latest malware detection techniques, available datasets, challenges, and limitations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.