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A Survey on Malware Detection with Deep Learning

  • Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

14 Atıf (Scopus)

Özet

Rapid development of Internet and technology has emerged a bunch of evolving malware and attack strategies. Therefore researchers focused on machine learning and deep learning methods to detect malware (viruses, bots, ransomware, trojans). In order to protect users from this treats many companies have been developing new algorithms and products. However, malware types have been increasing dramatically. Anti-malware producers have been detecting with millions of new malware types each year. So in order to stop that increase, there is an urgent need to develop new intelligent methods on malware detection. In this work, we have overviewed current intelligent machine learning and deep learning methods to solve malware detection. In this sense, we will present malware feature extraction and classification methods. Also, we will discuss more issues and challenges on that problem. Finally, we will share our foresight on malware detection methods.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıProceedings of the 13th International Conference on Security of Information and Networks, SIN 2020
EditörlerBerna Ors, Atilla Elci
YayınlayanAssociation for Computing Machinery
ISBN (Elektronik)9781450387514
DOI'lar
Yayın durumuYayınlandı - 4 Kas 2020
Etkinlik13th International Conference on Security of Information and Networks, SIN 2020 - Virtual, Online, Türkiye
Süre: 4 Kas 20206 Kas 2020

Yayın serisi

AdıACM International Conference Proceeding Series

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???event.eventtypes.event.conference???13th International Conference on Security of Information and Networks, SIN 2020
Ülke/BölgeTürkiye
ŞehirVirtual, Online
Periyot4/11/206/11/20

Bibliyografik not

Publisher Copyright:
© 2020 ACM.

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