Malware classification with using deep learning

Abstract

Today the use of electronic devices, which phones, computers, tablets, etc. has become more and more widespread. As a result of this situation, there is a great increase in the time spent on the internet. Although the widespread use of wireless communication brings about easier access to information, it can sometimes turn the security of data into a threat by malicious people. Malware that threatens information security can cause damage to electronic devices by damaging them, stealing personal information, loss of data of large companies, and causing financial and moral damages to users. For this reason, it has become more important to ensure the security of information while people share many data on the internet uncontrollably. Artificial intelligence methods, which have been developing rapidly in recent years, will undoubtedly become an indispensable part of information security in the near future. In this study, it is aimed to detect and classify malware families by using the Convolutional Neural Networks method, which is in the deep learning subfield of artificial intelligence.

Keywords

• Artificial Intelligence
• Convolutional Neural Network
• Deep Learning
• Malicious Software
• Malware Detection

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