<?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%">Michal Turčaník</style></author><author><style face="normal" font="default" size="100%">Martin Javurek</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cryptographic Key Generation by Genetic Algorithms</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%">cryptographic keys generation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">tree parity machine</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">54-61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;One of the security conditions of Vernam&amp;rsquo;s cipher is that the encryption key must be greater than or equal to the open text we want to encrypt. At the same time, this key must not be repeated in another encryption. Then, each change of the encryption key adds security to the encryption process. If a cipher is changed several times while encrypting a single open text, it becomes very difficult to decrypt the message. Therefore, our goal is to design a mechanism to generate an encryption key using a Tree Parity Machine and a Genetic Algorithm that will be able to create the same encryption keys on both sides that enter the encryption process. These keys should change during encryption. One of the first tasks is to create an input population for the genetic algorithm from the synchronized Tree parity machine. Therefore, this article presents one of the possible ways to create an input population without using too many synchronizing TPMs.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">54</style></section></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%">Todor Tagarev</style></author><author><style face="normal" font="default" size="100%">Petya Ivanova</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational Intelligence in Multi-Source Data and Information Fusion</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%">Computational Intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision Support</style></keyword><keyword><style  face="normal" font="default" size="100%">Forecasting</style></keyword><keyword><style  face="normal" font="default" size="100%">Fuzzy Logic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">MSDF</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Networks</style></keyword><keyword><style  face="normal" font="default" size="100%">Pattern Recognition</style></keyword><keyword><style  face="normal" font="default" size="100%">Soft Computing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><pages><style face="normal" font="default" size="100%">33-49</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A model of MultiSource Information Fusion (MSIF) is proposed. It expands the application of proven MSDF techniques to diverse problem areas. This model allows for a unified framework clearly distinguishing processing functions from methods dealing with partial, uncertain, and imprecise information. The concept of computational intelligence provides for a holistic approach to design and integration of methods and algorithms for information fusion. We describe the application of computational intelligence to the fusion of data and information in two studies of early warning. The emphasis is on the power of soft-computing methods in designing early warning architectures pertinent to forecasting events in complex dynamical systems. </style></abstract></record></records></xml>