Publication:
An Efficient Framework To Build Up Malware Dataset

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dc.contributor.authorMadihah Mohd Saudien_US
dc.contributor.authorZul Hilmi Abdullahen_US
dc.date.accessioned2024-05-28T05:57:27Z
dc.date.available2024-05-28T05:57:27Z
dc.date.issued2013
dc.descriptionVolume : 7 No:8en_US
dc.description.abstractThis research paper presents a framework on how to build up malware dataset. Many researchers took longer time to clean the dataset from any noise or to transform the dataset into a format that can be used straight away for testing. Therefore, this research is proposing a framework to help researchers to speed up the malware dataset cleaning processes which later can be used for testing. It is believed, an efficient malware dataset cleaning processes, can improved the quality of the data, thus help to improve the accuracy and the efficiency of the subsequent analysis. Apart from that, an in-depth understanding of the malware taxonomy is also important prior and during the dataset cleaning processes. A new Trojan classification has been proposed to complement this framework. This experiment has been conducted in a controlled lab environment and using the dataset from Vx Heavens dataset. This framework is built based on the integration of static and dynamic analyses, incident response method and knowledge database discovery (KDD) processes. This framework can be used as the basis guideline for malware researchers in building malware dataset.en_US
dc.identifier.doidoi.org/10.5281/zenodo.1086689
dc.identifier.epage459
dc.identifier.issn2010-376X
dc.identifier.issue8
dc.identifier.spage454
dc.identifier.urihttps://publications.waset.org/16150/an-efficient-framework-to-build-up-malware-dataset
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/6865
dc.identifier.volume7
dc.language.isoen_USen_US
dc.publisherWorld Academy of Science, Engineering and Technologyen_US
dc.relation.ispartofInternational Journal of Computer, Information Science and Engineeringen_US
dc.subjectDataset, knowledge database discovery (KDD), malware, static and dynamic analysesen_US
dc.titleAn Efficient Framework To Build Up Malware Dataseten_US
dc.typeArticleen_US
dspace.entity.typePublication

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