Pemanfaatan  Sequential Convolutional Neural Networks pada Deteksi  Malware Android

Winarnie Winarnie

doi:10.37601/jneti.v12i1.257

Winarnie Winarnie Politeknik Sawunggalih Aji

DOI: https://doi.org/10.37601/jneti.v12i1.257

Keywords: Sequential CNN, deteksi malware, deep learning, android

Abstract

Sistem operasi mobile yang paling banyak digunakan sekarang ini adalah Android . Kesuksesan android ini juga berdampak pada system keamanan data yang terancan dengan timbulnya penyebaran malware pada platform Android. Ada beberapa aplikasi yang menggunakan android pada google play store yang terkena malware. Malware ini dapat secara sembunyi-sembunyi membuat ponsel korbannya berlangganan dan membayar konten premium tanpa sepengetahuan korban. Penelitian deteksi malware Android ini sangat penting untuk menjaga keamanan dan privasi pengguna. karena proses identifikasi malware yang semakin rumit, maka diperlukan pendekatan deep learning untuk klasifikasi malware. Penelitian ini menggunakan metode sequential models untuk mendeteksi malware android. Hasil pengujian didapat hasil akurasi : 99.07%, presisi : 99.06%, recall : 98.32%, dan f1 score : 98.69%.

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