Malware is very dangerous while attacked a device system. The device that can be attacked by malware is a Mobile Phone such an Android. Antivirus in the Android device is able to detect malware that has existed but antivirus has not been able to detect new malware that attacks an Android device. In this issue, malware detection techniques are needed that can grouping the files between malware or non-malware (benign) to improve the security system of Android devices. Deep Learning is the proposed method for solving problems in malware detection techniques. Deep Learning algorithm such as Deep Neural Network has succeeded in resolving the malware problem by producing an accuracy rate of 99.42%, precision level 99% and recall 99.4%.
CITATION STYLE
Afifah, N., & Stiawan, D. (2019). The Implementation of Deep Neural Networks Algorithm for Malware Classification. Computer Engineering and Applications Journal, 8(3), 189–202. https://doi.org/10.18495/comengapp.v8i3.294
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