Please use this identifier to cite or link to this item: https://oarep.usim.edu.my/jspui/handle/123456789/1422
Title: Cyber terrorist detection by using integration of Krill Herd and Simulated Annealing algorithms
Other Titles: Intl. J. Adv. Comput. Sci. Appl.
Authors: Al-Sukhni H.A.H. 
Ahmad A.B. 
Saudi M.M. 
Alwi N.H.M 
Keywords: Cyber terrorists;Krill Herd;Simulating annealing;Web content classification
Issue Date: 2019
Publisher: Science and Information Organization
Journal: International Journal of Advanced Computer Science and Applications 
Abstract: 
This 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'. 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. � 2018 The Science and Information (SAI) Organization Limited.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070101082&partnerID=40&md5=e14830eb2f6191af0f2295cea6d965f8
ISSN: 2158107X
Appears in Collections:Scopus

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