Unmasking Memory Malware: A Comparative Analysis of Individual Machine Learning and Deep Learning using Ensemble Approaches

-, Samita Ramesh Babu (2024) Unmasking Memory Malware: A Comparative Analysis of Individual Machine Learning and Deep Learning using Ensemble Approaches. Masters thesis, Dublin, National College of Ireland.

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Abstract

Obfuscated Malware is malware that hides to avoid detection. Cyberattacks are constantly prevailing in recent years even sometimes it is undetected by antivirus software. The study involves detecting memory malware using machine and deep learning models using ensemble methods. The implementation is done by preprocessing and sampling of data of memory malware detection optimizing the representation of memory samples for effective analysis. Experiments were performed on a variety of machine learning algorithms and deep learning method, such as MLP Classifier, Adaboost, Gaussian Naive Bayes, Bagging classifier, SGD both individually and combined. Our findings reveal that ensemble methods performed compared to other models used in this research. Bagging classifier is outperformed individual algorithms by showing 92% accuracy. Then in combination of models Bagging and GNB showed 89% accuracy. The performance of these algorithms is evaluated based on metrics such as accuracy, precision, recall, and F1 score. This research can be guide for cybersecurity professionals seeking to implement efficient memory malware detection strategies.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Jayasekera, Evgeniia UNSPECIFIED
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 Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	15 Apr 2025 13:41
Last Modified:	15 Apr 2025 13:41
URI:	https://norma.ncirl.ie/id/eprint/7427

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