Publication:
Cyber Terrorist Detection by using Integration of Krill Herd and Simulated Annealing Algorithms

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dc.contributor.authorAl-Sukhni, HAHen_US
dc.contributor.authorBin Ahmad, Aen_US
dc.contributor.authorSaudi, MMen_US
dc.contributor.authorAlwi, NHMen_US
dc.date.accessioned2024-05-29T02:53:18Z
dc.date.available2024-05-29T02:53:18Z
dc.date.issued2019
dc.description.abstractThis paper presents a technique to detect cyber terrorists suspected activities over the net by integrating the Krill Herd and Simulated Annealing algorithms. Three new level of categorizations, including low, high, and interleave have been introduced in this paper to optimize the accuracy rate. Two thousand datasets had been used for training and testing with 10-fold cross validation for this research and the simulations were performed using Matlab (R). Based on the conducted experiment, this technique produced 73.01% accuracy rate for the interleave level; thus, outperforming the benchmark work. The findings can be used as a guidance and baseline work for other researchers with the same interest in this area.
dc.identifier.epage323
dc.identifier.isbn2156-5570
dc.identifier.issn2158-107X
dc.identifier.issue7
dc.identifier.scopusWOS:000485682500045
dc.identifier.spage317
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/11381
dc.identifier.volume10
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherScience & Information Sai Organization Ltden_US
dc.relation.ispartofInternational Journal Of Advanced Computer Science And Applications
dc.sourceWeb Of Science (ISI)
dc.subjectKrill Herden_US
dc.subjectweb content classificationen_US
dc.subjectcyber terroristsen_US
dc.subjectsimulating annealingen_US
dc.titleCyber Terrorist Detection by using Integration of Krill Herd and Simulated Annealing Algorithmsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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