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Article title NEURAL NETWORK ANALYSIS OF SECURITY EVENTS IN INFORMATION SYSTEM
Authors A.V. Nikishova, R.F. Rudikov, E.A. Kalinina
Section SECTION II. SECURITY OF INFORMATION SYSTEMS AND NETWORKS
Month, Year 02, 2014 @en
Index UDC 004.056
DOI
Abstract Statistics for 2013 and predictions for 2014 relative to the attacking impacts on the information system shows the growth of emerging attacking impacts from a number of known and also the growth of new designs and directions of implementation of attacks. In this regard, the urgent task is to gather information about events occurring in the information system and related to the main objects of the information system and conducting effective analysis. The main requirements to the analysis means are: speed and the ability to adapt to new circumstances - adaptability. The means that can satisfy these requirements are in artificial intelligence systems. In particular there are a number of studies, using neural networks as a tool of analysis. There are different types of neural networks, which differ depending on the task and more suitable for various input data. The multi-agent intrusion detection system engaged in the collection and analysis of the collected information about the events of the information system with two types of neural networks has been built. For analysis of various objects’ of the information system logs multilayer perceptron is used. For analysis directly collected information about events of information system’s objects the Jordan’s network is used. Application of multi-agent intrusion detection system allows increasing the security of the information system.

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Keywords Neural network; multilayer perceptron; security event; attacks; intrusion detection system; multi-agent intrusion detection system.
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