Classifying malwares for identification of author groups
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hong, Jiwon | - |
dc.contributor.author | Park, Sanghyun | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.contributor.author | Kim, Dongphil | - |
dc.contributor.author | Kim, Wonho | - |
dc.date.accessioned | 2022-07-12T13:52:03Z | - |
dc.date.available | 2022-07-12T13:52:03Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2018-02 | - |
dc.identifier.issn | 1532-0626 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/150625 | - |
dc.description.abstract | Malwares are growing exponentially in number, and authors of malwares are continuously releasing new ones. Malwares developed by the same author group might have similar signatures. For a number of applications including digital forensic and law enforcement, such characteristics can be used to determine which author group is likely to have released a given malware. In this paper, we describe a new type of classification that identifies which group of authors is most likely to have developed a given malware. We identify and verify a set of various features obtained through static and dynamic analyses of malwares and exploit them for classification. We evaluate our approach through extensive experiments with a real-world dataset labeled by a group of domain experts. The results show that our approach is effective and provides good accuracy in malware classification. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | WILEY | - |
dc.title | Classifying malwares for identification of author groups | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.identifier.doi | 10.1002/cpe.4197 | - |
dc.identifier.scopusid | 2-s2.0-85026436057 | - |
dc.identifier.wosid | 000419780000006 | - |
dc.identifier.bibliographicCitation | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, v.30, no.3 | - |
dc.relation.isPartOf | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE | - |
dc.citation.title | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE | - |
dc.citation.volume | 30 | - |
dc.citation.number | 3 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordAuthor | dynamic analysis | - |
dc.subject.keywordAuthor | feature extraction | - |
dc.subject.keywordAuthor | malware classification | - |
dc.subject.keywordAuthor | static analysis | - |
dc.identifier.url | https://onlinelibrary.wiley.com/doi/10.1002/cpe.4197 | - |
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