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Мониторинг состояний катастрофоустойчивой информационной системы с помощью гибридной иммунной сети

Мониторинг состояний катастрофоустойчивой информационной системы с помощью гибридной иммунной сети

Abstract

Цель исследования: разработка методики классификации состояний катастрофоустойчивой системы с использованием гибридной иммунной сети. В рамках данного исследования решены следующие задачи: обоснована значимость обеспечения катастрофоустойчивости информационной системы в процессе управления информационной безопасностью организации в целом; предложен подход к процессу проведения мониторинга и контроля за показателями катастрофоустойчивости системы. Разработана и формально описана гибридная иммунная сеть, с применением алгоритмов клонального и «положительного» отбора и областью покрытия, образованной двумя типами детекторов. Сделан вывод о возможности применения разработанного подхода в процессе анализа катастрофоустойчивости информационных систем.

The purpose of the study is development of technique classification states of disaster recovery systems using a hybrid immune network. This study addressed the following objectives: to substantiate the importance of ensuring disaster recovery information system in the management of information security in general, the approach to the process of monitoring and performance monitoring disaster recovery system. The hybrid immune network is developed and formally described, using algorithms clonal and "positive" selection and coverage area formed by the two types of detectors. The conclusion about possibility of using the developed approach in the analysis of information systems disaster recovery.

Keywords

КАТАСТРОФОУСТОЙЧИВОСТЬ, ИНФОРМАЦИОННЫЕ СИСТЕМЫ, ИСКУССТВЕННАЯ ИММУННАЯ СЕТЬ, КЛОНАЛЬНЫЙ ОТБОР, «ПОЛОЖИТЕЛЬНЫЙ» ОТБОР, МОНИТОРИНГ, ИНФОРМАЦИОННАЯ БЕЗОПАСНОСТЬ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average