<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dimitar Kamenov</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Intelligent Methods for Big Data Analytics and Cyber Security</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">cyber security</style></keyword><keyword><style  face="normal" font="default" size="100%">data mining</style></keyword><keyword><style  face="normal" font="default" size="100%">filtering</style></keyword><keyword><style  face="normal" font="default" size="100%">human factor</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">network graphs</style></keyword><keyword><style  face="normal" font="default" size="100%">outlier detection</style></keyword><keyword><style  face="normal" font="default" size="100%">semantic analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial data mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">statistical analysis</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">255-262</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The article examines some intelligent computational methods for big data analysis which are applicable to issues of cyber security and military science, including the analysis of hybrid threats. It presents and compares big data analysis techniques such as quantitative analysis, qualitative analysis, data mining, statistical analysis, machine learning, semantic analysis, and visual analysis. The importance and prospects of intelligent methods for big data analysis are emphasized.
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