Abstract. In article the literature analysis concerning determination of intellectuality of systems of information security is made. As a result of the analysis the conclusion expansion of concept of intellectuality of systems of information security is drawn. New classification which gives a view of this problem much more widely is given.Keywords: intellectual systems of information security, intellectuality levels. Введение.В настоящее время в области информационной безопасности автоматизированных систем обработки данных (АСОД) особое внимание уделяется вопросу проектирования интеллектуальных систем защиты информации (ИСЗИ). Одним из существенных факторов характеризующих ИСЗИ является степень (уровень) интеллектуальности систем защиты информации. В существующей литературе делались и делаются попытки определения понятия интеллектуальности систем защиты информации. Некоторые полученные результаты в области искусственного интеллекта представляют собой как теоретический, так и практический интерес. Наиболее интересные и существенные результаты, с точки зрения их адаптации к системам защиты информации приведены в работах [1,2]. Однако, анализ публикаций в этой области и полученные результаты не дают должного представления о полноте или значимости решаемых задач по проектированию ИСЗИ. Работа поддержана грантом РФФИ 13-01-00544.
In the article there is represented and solved the problem of space images recognition for the presence of solid household and industrial waste without binarization. The methods of stochastic geometry and mathematical analysis are used. In the work there is proposed an algorithm based on a trace transformation using discrete orthogonal transformations (DOT) to minimize the attribute space and carry out studies on correctness by Tikhonov. For the implementation of the algorithm there are used elements of mathematical analysis, wavelet analysis, functional analysis, theory of discrete orthogonal transformations, methods for deciphering space images in the problem of stochastic scanning of space images based on the formation of a triplet attribute with minimization of attribute space using DOT. The development a trace matrices and the selection of informative features by stochastic geometry to find WDF from high-resolution space images are investigated from the point of view of DOT apparatus application. A study of the sustainability task was also performed. The proposed technique was tested using the example of space photographs with a WDF image. Conclusions are drawn on the use of the method proposed in this article for the task of automatic computer generation and selection of informative features for determining waste disposal facilities from high-resolution space images. It is proposed to use the Tikhonov regularization method to introduce stability in this task.
This article is dedicated to the problem of detecting intrusions of unknown type based on neural networks that bypass the system of information security in automated data processing systems and are not recognized as spiteful. Development of the means, methods and measures for detecting or preventing such hidden attacks is of particular relevance. Methodological research on the development of procedure for detecting intrusions are based on the achievements of systemic analysis, systemic-conceptual approach towards protection of information in automated data processing systems and achievements of the theory of neural systems in the area of ensuring information security. The object of this research is the intrusions of unknown type in automated data processing systems. The subject is the neural networks, namely neural networks of direct action. The main result lies in the development of neural network of direct action in form of the diagram of neural network links for detecting intrusions. For solving this task, the author developed: 1) The system of input indicators of the neural system; 2) Scales for the assessment of values of the formed indicators; 3) General procedure for detecting intrusions based on neural networks, the essence of which consists in implementation of the following sequence of actions: a) formation of the list of all the main parties to the process of detection of intrusion; b) formation of the set of parameters that characterize each of them; c) formation of the set of numerical characteristics for each parameter using the assessment scales of the formed indicators; d) analysis of the parameters of the configuration of neural network The developed procedure may serve as the basic in further practical developments of the concept of detecting intrusions of unknown types based on neural networks.
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