<?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%">Elitsa Pavlova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Implementation of Federated Cyber Ranges  in Bulgarian Universities: Challenges, Requirements, and Opportunities</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%">Bulgaria</style></keyword><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">cyber range</style></keyword><keyword><style  face="normal" font="default" size="100%">Education</style></keyword><keyword><style  face="normal" font="default" size="100%">functionalities</style></keyword><keyword><style  face="normal" font="default" size="100%">training</style></keyword><keyword><style  face="normal" font="default" size="100%">University</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">149-159 </style></pages><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;margin-left:20.15pt;&quot;&gt;Cyber education has been one of the global challenges in recent years. Attacks are becoming more sophisticated, and it is increasingly difficult to provide a safe working environment. Hyper-realistic virtual environments called cyber ranges help increase the level of cybersecurity training. Access to multi-domain exercises is needed to make full use of their capabilities, combine information technology networks and other appropriate infrastructure. A systematic review of the modern cyber ranges used for teaching and research purposes in higher education institutions has been made. This study aims to analyse cyber range characteristics, functionalities, and requirements for their implementation and integration in accordance with the EU regulations. The results will be used in the development of a conceptual model for a cybersecurity training laboratory at the University of National and World Economy, Sofia, Bulgaria. Its inclusion in the teaching and research process is a relevant, important, and promising area for the future of higher educaiton in cybersecurity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record><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.
</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Veselin Monev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Enterprise IT security metrics: Classification, examples and characteristics (in Bulgarian)</style></title><secondary-title><style face="normal" font="default" size="100%">IT4Sec Reports</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">characteristics</style></keyword><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">company</style></keyword><keyword><style  face="normal" font="default" size="100%">expected annual lose</style></keyword><keyword><style  face="normal" font="default" size="100%">incident</style></keyword><keyword><style  face="normal" font="default" size="100%">IT security</style></keyword><keyword><style  face="normal" font="default" size="100%">management</style></keyword><keyword><style  face="normal" font="default" size="100%">matrix</style></keyword><keyword><style  face="normal" font="default" size="100%">measure</style></keyword><keyword><style  face="normal" font="default" size="100%">Metric</style></keyword><keyword><style  face="normal" font="default" size="100%">metrics</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk</style></keyword><keyword><style  face="normal" font="default" size="100%">Vulnerabilities</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">March 2014</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">111</style></number><publisher><style face="normal" font="default" size="100%">Institute of Information and Communication Technologies</style></publisher><pub-location><style face="normal" font="default" size="100%">Sofia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The report addresses the key issues associated with measuring IT security for private companies. Several classifications of metrics are discussed focusing on the functions of different levels of security management. For the most part, this work examines the pros and cons of common metrics for measuring IT security and provides guidelines for creating own metrics. ‘Own metrics,’ adapted to the corporate environment, are those which security managers have to create and use for the purpose of effective management.</style></abstract></record></records></xml>