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Packer Detection using visualisation

Kolarikkal, Norman (2021) Packer Detection using visualisation. Masters thesis, Dublin, National College of Ireland.

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Abstract

Malware is software for harming a computer system. Current methods for detecting malware heavily use signatures such as hashes. However, these methods can easily be deceived using methods such as packing. We, therefore, proposed use of visualization and Convolutional Neural network (CNN) model to detect and classify packers as well to detect if a packed sample is malicious or benign. We would be converting image to a RGB image and then use CNN on the images to classify packed samples. Our model was able to work on multiple types of files with us testing our algorithm on exe files and apk files.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software > Computer Security
T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions: School of Computing > Master of Science in Cyber Security
Depositing User: Clara Chan
Date Deposited: 01 Nov 2021 11:42
Last Modified: 01 Nov 2021 11:42
URI: https://norma.ncirl.ie/id/eprint/5118

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