Cited 0 time in
Malware analysis method using visualization of binary files
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Han, Kyoungsoo | - |
| dc.contributor.author | Lim, Jae Hyun | - |
| dc.contributor.author | Im, Eul Gyu | - |
| dc.date.accessioned | 2022-07-16T07:55:11Z | - |
| dc.date.available | 2022-07-16T07:55:11Z | - |
| dc.date.created | 2021-05-13 | - |
| dc.date.issued | 2013-10 | - |
| dc.identifier.issn | 0000-0000 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/161780 | - |
| dc.description.abstract | Malware authors have been generating and disseminating malware variants through various ways, such as reusing modules or using automated malware generation tools. With the help of the malware generation techniques, the number of malware keeps increasing every year. Therefore, new malware analysis techniques are needed to reduce malware analysis overheads. Recently several malware visualization methods were proposed to help malware analysts. In this paper, we proposed a novel method to visually analyze malware by transforming malware binary information into image matrices. Our experimental results show that the image matrices of malware can effectively classify malware families. | - |
| dc.language | 영어 | - |
| dc.language.iso | en | - |
| dc.publisher | Association for Computing Machinary, Inc. | - |
| dc.title | Malware analysis method using visualization of binary files | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Im, Eul Gyu | - |
| dc.identifier.doi | 10.1145/2513228.2513294 | - |
| dc.identifier.scopusid | 2-s2.0-84891431181 | - |
| dc.identifier.bibliographicCitation | Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013, pp.317 - 321 | - |
| dc.relation.isPartOf | Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 | - |
| dc.citation.title | Proceedings of the 2013 Research in Adaptive and Convergent Systems, RACS 2013 | - |
| dc.citation.startPage | 317 | - |
| dc.citation.endPage | 321 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Conference Paper | - |
| dc.description.journalClass | 1 | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordPlus | Binary information | - |
| dc.subject.keywordPlus | Generation techniques | - |
| dc.subject.keywordPlus | Generation tools | - |
| dc.subject.keywordPlus | Malware analysis | - |
| dc.subject.keywordPlus | Malware detection | - |
| dc.subject.keywordPlus | Malware families | - |
| dc.subject.keywordPlus | Malwares | - |
| dc.subject.keywordPlus | Visualization method | - |
| dc.subject.keywordPlus | Visualization | - |
| dc.subject.keywordPlus | Computer crime | - |
| dc.subject.keywordAuthor | malware analysis | - |
| dc.subject.keywordAuthor | malware detection | - |
| dc.subject.keywordAuthor | malware similarity | - |
| dc.subject.keywordAuthor | malware visualization | - |
| dc.identifier.url | https://dl.acm.org/doi/10.1145/2513228.2513294 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1366
COPYRIGHT © 2024 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
