Informatics and Applications
2019, Volume 13, Issue 4, pp 81-84
CONCEPTS FORMING ON THE BASIS OF SMALL SAMPLES
- A. A. Grusho
- M. I. Zabezhailo
- N. A. Grusho
- E. E. Timonina
Abstract
Monitoring systems of information security of information systems obtain information in the form of chains of short messages which can be considered as chains of small samples. Often, owing to an inertance of information systems, these chains reflect close statuses of the computing system or network. In the paper, it is supposed that work of the system can be presented in the form of a finite set of modes which are called concepts. Violations of security are detected by means of anomalies that are associated with emergence of new concepts. The known technologies of identification of anomalies are based on creation of a model of a normal system's behavior. Concepts correspond to normal types of a system's behavior. In the paper, the problem of creation of concepts on the basis of machine learning based on chains of small samples is considered. The algorithm of concepts forming is constructed and its efficiency is proved.
[+] References (7)
- Grusho, A., N. Grusho, E. Timonina, and S. Shorgin.
2015. Vozmozhnosti postroeniya bezopasnoy arkhitektury dlya dinamicheski izmenyayushcheysya informatsionnoy sistemy [Possibilities of secure architecture creation for dynamically changing information systems]. Sistemy i Sredstva Informatiki - Systems and Means of Informatics 25(3):78-93.
- Grusho, A., N. Grusho, and E. Timonina. 2019. The bans in finite probability spaces and the problem of small samples. Distributed computer and communication networks. Eds. V. M. Vishnevskiy, K. E. Samouylov, and
D. V. Kozyrev. Lecture notes in computer science ser. Springer. 11965:578-590.
- Tukey, J. W 1977. Exploratory data analysis. Addison Wes-ley. 711 ð.
- Grusho, A., N. Grusho, and E. Timonina. 2016. Detection of anomalies in non-numerical data. 8th Congress (Inter-national) on Ultra Modern Telecommunications and Control Systems and Workshops Proceedings. Piscataway, NJ: IEEE. 273-276.
- Jordan, M. I., and T. M. Mitchell. 2015. Machine learning: Trends, perspectives, and prospects. Science 349(6245): 255-260.
- Bramley, N. R. 2017. Constructing the world: Active causal learning in cognition. London: University College London. PhD Thesis. 361 p.
- Shu, J., X. Zongben, and M. Deyu. 2018. Small sample learning in big data era. Available at: https://arxiv.org/ abs/1808.04572 (accessed October 9, 2019).
[+] About this article
Title
CONCEPTS FORMING ON THE BASIS OF SMALL SAMPLES
Journal
Informatics and Applications
2019, Volume 13, Issue 4, pp 81-84
Cover Date
2019-12-30
DOI
10.14357/19922264190413
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
information security monitoring; small samples; small sample learning; concepts forming
Authors
A. A. Grusho , M. I. Zabezhailo , N. A. Grusho , and E. E. Timonina
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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