Publication:
The Design and Development of Spam Risk Assessment Prototype: In Silico of Danger Theory Variants

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dc.contributor.authorZainal, Ken_US
dc.contributor.authorJali, MZen_US
dc.date.accessioned2024-05-29T02:52:14Z
dc.date.available2024-05-29T02:52:14Z
dc.date.issued2017
dc.description.abstractNow-a-days, data is flowing with various types of information and it is absolutely enormous and moreover, it is in unstructured form. These raw data is meaningless unless it is processed and analyzed to retrieve all the valuable and meaningful information. In this paper, a design and principal functionalities of the system prototype is introduced. A process of information retrieval by applying the text mining with Artificial Immune System (AIS) is proposed to discover the possible level of severity for a Short Messaging Service (SMS) spam. This is expected to be a potential tool in retrieving an implicit danger that a spam might impact to the recipients. Furthermore, the development of this tool can be considered as an emergence of another data mining tool that also exceedingly possible to be embedded with another existing tool.
dc.identifier.epage410
dc.identifier.isbn2156-5570
dc.identifier.issn2158-107X
dc.identifier.issue4
dc.identifier.scopusWOS:000403339400054
dc.identifier.spage401
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/11288
dc.identifier.volume8
dc.languageEnglish
dc.language.isoen_US
dc.publisherScience & Information Sai Organization Ltden_US
dc.relation.ispartofInternational Journal Of Advanced Computer Science And Applications
dc.sourceWeb Of Science (ISI)
dc.subjectDanger Theory Variantsen_US
dc.subjectText Spam Messagesen_US
dc.subjectSeverity Assessmenten_US
dc.subjectText Miningen_US
dc.subjectInformation Retrievalen_US
dc.subjectKnowledge Discoveryen_US
dc.titleThe Design and Development of Spam Risk Assessment Prototype: In Silico of Danger Theory Variants
dc.typeArticleen_US
dspace.entity.typePublication

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