Naslov
Machine Learning for Malware Analysis: Methods, Challenges, and Future Directions

Autori
Yadav, Krishna ; Sethi, Aarushi ; Kaur, Mavneet ; Perakovic, Dragan

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, ostalo

Knjiga
Advances in Malware and Data-Driven Network Security

Urednik/ci
Gupta, Brij

Izdavač
IGI Global

Grad
Hershey (PA)

Godina
2022

Raspon stranica
1-18

ISSN
1948-9730

Ključne riječi
Machine Learning ; Malware Analysis ; Methods ; Challenges ; Future Directions

Sažetak
Companies and organizations are collecting all sorts of data ranging from nominal feedback like customer reviews to highly classified data like medical records. With data being such a critical aspect of most of the operations around us, cybercriminals are looking for an opportunity to misuse this information. One such device that cybercriminals use to further their malicious intent is malware. Over the years, these cybercriminals have become immensely powerful using the knowledge of previous attacks. Hence, malware analysis and methods to troubleshoot the problems arising due to malware attacks is the need of the hour. Over time, different new approaches have been developed to defend malware. However, in recent times, machine learning-based malware analysis has gained popularity. The capacity to detect possible future malware by learning from existing malware patterns makes this method very popular. In this chapter, the authors have introduced different malware and the machine learning-based approach that has been developed in recent times to mitigate malware.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Tehnologija prometa i transport, Informacijske i komunikacijske znanosti

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