Deep Learning Approaches to Malware Detection and Classification

Abstract

The paper is framed to evaluate the effectiveness and the application of the use of machine learning and deep learning techniques for the purpose of detection of malware. In the recent times where cyber networks play a pivotal role to gather and analyze data, malware is a harmful element and an element of concern. In present times algorithms of deep learning such as CNN and RNN are highly effective to detect malware and to safeguard the cyber networks from harmful practices. The trends of these practices are evaluated in great vigor and how these algorithms are useful in the evolution of cyber security is also analyzed in this assignment.