Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Detection of botnets before activation: an enhanced honeypot system for intentional infection and behavioral observation of malware

Full metadata record
DC Field Value Language
dc.contributor.authorMoon, Young Hoon-
dc.contributor.authorKim, Eunjin-
dc.contributor.authorHur, Suh Mahn-
dc.contributor.authorKim, Huy Kang-
dc.date.accessioned2021-09-06T15:07:20Z-
dc.date.available2021-09-06T15:07:20Z-
dc.date.created2021-06-15-
dc.date.issued2012-10-
dc.identifier.issn1939-0114-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/107378-
dc.description.abstractAs botnets have become the primary means for cyber attacks, how to detect botnets becomes an important issue for researchers and practitioners. In this study, we introduce a system that is designed to detect botnets prior to their activation. Pre-detection of botnets becomes available with our enhanced honeypot system that allows us to intentionally infect virtual machines in honeynets. For empirical testing, we applied our system to a major Internet service provider in Korea. After running our proposed system for 12?months, it was found that nearly 40% of blacklisted botnets were pre-detected by our system before their attacks begin. We expect that our system can be used to detect command-and-control servers and to screen them out during their propagation stage before they make harmful attacks. Copyright (c) 2012 John Wiley & Sons, Ltd.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherWILEY-BLACKWELL-
dc.titleDetection of botnets before activation: an enhanced honeypot system for intentional infection and behavioral observation of malware-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Huy Kang-
dc.identifier.doi10.1002/sec.431-
dc.identifier.scopusid2-s2.0-84867625328-
dc.identifier.wosid000309238700003-
dc.identifier.bibliographicCitationSECURITY AND COMMUNICATION NETWORKS, v.5, no.10, pp.1094 - 1101-
dc.relation.isPartOfSECURITY AND COMMUNICATION NETWORKS-
dc.citation.titleSECURITY AND COMMUNICATION NETWORKS-
dc.citation.volume5-
dc.citation.number10-
dc.citation.startPage1094-
dc.citation.endPage1101-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaTelecommunications-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryTelecommunications-
dc.subject.keywordAuthorbotnet detection-
dc.subject.keywordAuthormalware-
dc.subject.keywordAuthorhoneynets-
dc.subject.keywordAuthorintentional infection-
dc.subject.keywordAuthorbehavioral analysis-
Files in This Item
There are no files associated with this item.
Appears in
Collections
School of Cyber Security > Department of Information Security > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE