An Evaluation and Performance study on BODMAS dataset for Malware Analysis

Rayankula, Bhargav Chowdary (2023) An Evaluation and Performance study on BODMAS dataset for Malware Analysis. Masters thesis, Dublin, National College of Ireland.

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Abstract

Malware The field of malware analysis has been an essential part of the cybersecurity industry, as it enables the detection, classification, and mitigation of malware. As the malware landscape has evolved rapidly over the years, so have the techniques and tools used to analyze it. The use of datasets for malware analysis has become increasingly prevalent, as they offer researchers and practitioners a reliable and scalable means of assessing the effectiveness of various approaches. This thesis report focuses on the evaluation and performance study of the BODMAS dataset for malware analysis. The dataset comprises a diverse range of malware samples, including viruses, worms, and trojans, that have been collected from various sources. The aim of this study is to assess the usefulness of the BODMAS dataset for malware analysis and to evaluate the performance of various analysis tools and techniques using this dataset. To achieve this, firstly, the BODMAS dataset is analyzed and its properties are characterized., such as the distribution of malware families and the prevalence of specific features. Then, the performance of several state-of-the-art malware analysis techniques, including static analysis and dynamic analysis, is evaluated using the BODMAS dataset. Finally, insights into the strengths and weaknesses of the BODMAS dataset are provided, and its potential applications in malware analysis research are discussed. Overall, this thesis report contributes to the ongoing efforts to develop better tools and techniques for malware analysis and provides valuable insights into the usefulness of datasets
in this field.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Moldovan, Arghir-Nicolae 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
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Tamara Malone
Date Deposited:	15 Jan 2024 16:52
Last Modified:	15 Jan 2024 16:52
URI:	https://norma.ncirl.ie/id/eprint/6915

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