Robust Malware Detection using Residual Attention Network

Ganesan, Shamika; R, vinayakumar; Krichen, Moez; V, Sowmya; Alroobaea, Roobaea; KP, Soman

doi:10.36227/techrxiv.13385291.v1

Residual_IEEE.pdf (2.36 MB)

Robust Malware Detection using Residual Attention Network

preprint

posted on 2020-12-18, 13:58 authored by Shamika Ganesan, vinayakumar Rvinayakumar R, Moez KrichenMoez Krichen, Sowmya V, Roobaea Alroobaea, Soman KP

In this paper, we explore the use of an attention based mechanism known as Residual Attention for malware detection and compare this with existing CNN based methods and conventional Machine Learning algorithms with the help of GIST features. The proposed method outperformed traditional malware detection methods which use Machine Learning and CNN based Deep Learning algorithms, by demonstrating an accuracy of 99.25%.