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Automated PE32 Threat Classification using Import Table and Deep Neural Networks

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13 Feb 2020CPOL17 min read 15.2K   8  
In this research, we are going to prove that Import Address Table is very helpful in classifying a malware.
A malware is a computer program which harms the computer in which it gets executed. Malware analysis plays a major role in analysing the functionalities and behaviour of the malware. Malware analysis is a slow and tedious process which involves a lot of manual work. Finding the type of the malware will often boost up the analysis process and helps the researcher to know what the binary is capable of. Usually, researchers perform various static analysis techniques to find the category of the malware using various tools like strings, dependency walker, etc. But each day. there are millions [1] of new malware that get released, so classifying them manually is a non-feasible solution. In our approach, we are going to automate this process using deep neural networks.

This article is an entry in our Machine Learning and Artificial Intelligence Challenge. Articles in this sub-section are not required to be full articles so care should be taken when voting.

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


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