Parallel to the adoption of mobile technology in our daily lives, there is a growing and increasing proliferation of cyber frauds and malicious content. Mobile malware can exploit the vulnerabilities of the device, modify, disclose or erase confidential data, such as credit card numbers, passwords, medical data, contacts, or even block the device asking for a ransom. In this paper, we leverage the possibilities of deep fully-connected neural networks, using permissions and Application Programming Interfaces APIs as features, to automatically and efficiently detect Android malware. We achieved a score of 88.9\% using a feed-forward of 128x128x1, 2-hidden layers configuration.
Neural networks Android Malware Detection Smartphone Security
The authors would like to thank the Koodous administrators for their effort in collecting and sharing the academic malware dataset.
Birincil Dil | İngilizce |
---|---|
Konular | Yazılım Mühendisliği (Diğer) |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 5 Haziran 2021 |
Kabul Tarihi | 9 Aralık 2020 |
Yayımlandığı Sayı | Yıl 2021 Cilt: 4 Sayı: 1 |
International Journal of Informatics and Applied Mathematics