Asthe technology trend in the recent years uses the systems with network bases, it is crucial to detect them from threats. In this study, the following methods are applied for detecting the network attacks: support vector machine (SVM) classifier, artificial Neural Networks (ANN), and Genetic Algorithms (GA). The objective of this study is to compare the outcomes of GA with SVM and GA with ANN and thencomparing the outcomes of GA with SVM and GA with ANN and other algorithms. Knowledge Discovery and Data Mining (KDD CPU99) data set has been used in this paper for obtaining the results.

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Abstract.Wireless capsular endoscopy is a novel method of gastroenterology investigation during last years. Most important as well as the most difficult part of such investigation is the blood artefact determination. These artefacts are only be localised by medical experts trained in such field of gastroenterology medicine. This article describe the process of development a software solution which can be used to help localise some specific artefacts using developed algorithms. Such algorithms are firstly developed by Matlab solution while they are consequently transformed to developed software solution. Our solution was already preliminary tested by one of specific artefacts -blood artefacts, while the results have been found as sufficient to several use of this software. Future research will be focussed on other specific artefact description and algorithm development for detection.

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