Image malware detection using deep learning

Abstract

We are currently living in an area where artificial intelligence is making out every day to day life much easier to manage. Some researchers are continuously developing the codes of artificial intelligence to utilize the benefits of the human being. And there is the process called data mining, which is used in many domains, including finance, engineering, biomedicine, and cyber security. The utilization of data mining, artificial intelligence algorithms like deep learning is so vast that we can't even name them all. This technology has almost touched every industry and cyber security is the most beneficial. The process of enhancing cyber security with the help of deep learning methods has come out of the theory books and many organizations are utilizing them rather than using a traditional piece of software to defend against online threats. Especially in the field of recognizing and classifying codes or malware. And this is essential, because, with the advent of cloud computing and the Internet of Things, expand potential malware infection sites from PCs to any electronic device. This makes our day to day life very unsafe. In this post, first, we will describe in brief how deep learning can be the most useful and promising techniques to detect malware. Besides this we will go through a deep neural network,ResNet for malware dynamic behavior classification jobs.

Mobile Malware Behaviour through Opcode Analysis

“…Next, the binaries will then be decompiled to obtain the opcodes sequence. In a study done by [37], the researchers implemented the static analysis and uses deep learning to detect malware. The malware undergoes a process of unpacking where the opcode is extracted and later converted into binary image.…”

Evolution of Malware Threats and Techniques: a Review

“…Nowadays the malware industry has become very profitable which attracted more efforts by cyber criminals and caused an exponential growth in the numbers, types, and complexity of malware created [4]. Moreover, generic anti-virus software alone is unable to detect malware mutations and its variants which makes the user and system vulnerable at any given time [5]. Malware is mainly divided into two categories: first-generation malware or static malware and second-generation malware or dynamic malware Malware is mainly divided into two categories: first-generation malware or static malware and second-generation malware or dynamic malware [6].…”