Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/1365
DC FieldValueLanguage
dc.contributor.authorChan, Anthony Hing-Hungen_US
dc.contributor.otherMohammed, M. M. Z. E.-
dc.contributor.otherVentura, N.-
dc.contributor.otherHashim, M.-
dc.contributor.otherAmin, I.-
dc.date.accessioned2021-08-20T07:44:47Z-
dc.date.available2021-08-20T07:44:47Z-
dc.date.issued2009-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/1365-
dc.description.abstractInternet worms pose a major threat to institutions, companies, organizations, universities, and the like, and their destruction causes loss of millions of dollars. Therefore, the networks must be protected as much as possible to avoid losses. In this paper we propose automatic and accurate system for signature generation for unknown polymorphic worms. We have designed a novel double-honeynet system, which is able to detect new worms that have not been seen before. The system is based on a modified Knuth-Morris-Pratt Algorithm that uses polymorphic worm substrings to find multiple invariant substrings that are shared between all polymorphic worm instances and use them as signatures. The system is able to generate accurate signatures for single and multiple worms.en_US
dc.language.isoenen_US
dc.publisherCSREA Pressen_US
dc.titleA modified Knuth-Morris-Pratt Algorithm for zero-day polymorphic worms detectionen_US
dc.typeconference proceedingsen_US
dc.relation.publicationProceedings of the 2009 International Conference on Security and Management (SAM)en_US
dc.contributor.affiliationSchool of Computing and Information Sciencesen_US
dc.relation.isbn1601321260en_US
dc.cihe.affiliatedNo-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairetypeconference proceedings-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.cerifentitytypePublications-
crisitem.author.deptYam Pak Charitable Foundation School of Computing and Information Sciences-
crisitem.author.orcid0000-0001-7479-0787-
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