Android malware detection using hybrid ANFIS architecture with low computational cost convolutional layers

BACKGROUND: Android is the most widely used operating system all over the world. Due to its open nature, the Android operating system has become the target of malicious coders. Ensuring privacy and security is of great importance to Android users. METHODS: In this study, a hybrid architecture is pro...

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Detalles Bibliográficos
Autores principales: Atacak, İsmail, Kılıç, Kazım, Doğru, İbrahim Alper
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575934/
https://www.ncbi.nlm.nih.gov/pubmed/36262124
http://dx.doi.org/10.7717/peerj-cs.1092

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575934/
https://www.ncbi.nlm.nih.gov/pubmed/36262124
http://dx.doi.org/10.7717/peerj-cs.1092

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