AndroAnalyzer: android malicious software detection based on deep learning

ARSLAN R. S.

PEERJ COMPUTER SCIENCE, cilt.7, ss.1-20, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7
  • Basım Tarihi: 2021
  • Doi Numarası: 10.7717/peerj-cs.533
  • Dergi Adı: PEERJ COMPUTER SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-20
  • Kayseri Üniversitesi Adresli: Hayır

Özet

Background: Technological developments have a significant effect on the development of smart devices. The use of smart devices has become widespread due to their extensive capabilities. The Android operating system is preferred in smart devices due to its open-source structure. This is the reason for its being the target of malware. The advancements in Android malware hiding and detection avoidance methods have overridden traditional malware detection methods.