Big Data Analysis Methods Based on Machine Learning to Ensure Information Security
| Autor: | Veselska Olga, Ziubina Ruslana, Fіnenko Yuriy, Nikodem Joanna |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Principal (computer security) Big data Information security Object (computer science) Machine learning computer.software_genre Statistical classification Search algorithm Information system General Earth and Planetary Sciences Data Protection Act 1998 Artificial intelligence business computer General Environmental Science |
| Zdroj: | KES |
| ISSN: | 1877-0509 |
| Popis: | In this article the methods of data mining which is the basis of modern search algorithms are considered. The classification of machine learning methods is carried out and the principal difference between them is shown. Mathematical aspects of object classification are described. Possibilities of application of algorithms of machine learning for protection of information systems are considered. The concept of building a new method of primary information analysis is offered. Theoretical bases of machine learning and image recognition in conditions of incomplete a priori information about classes are considered and systematized. The scheme of practical application of theoretical classification algorithms based on real input data is shown. The result of the research showed the possibility of using machine learning technologies for data protection with the help of data mining to reveal hidden embedded information in the object of research. |
| Databáze: | OpenAIRE |
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