The Technique of Multi-aspect Evaluation and Categorization of Malicious Information Objects on the Internet
https://doi.org/10.31854/1813-324X-2019-5-3-58-65
Abstract
Under the influence of rapid development in the sphere of information technologies, rises the challenge related to detection of malicious information sources on the Internet. To solve this we can use machine learning methods as one of the most popular and powerful tools designed to identify dependencies between input (observed) data and output (desired) results. This article presents a methodology which is aimed at multi-level processing of input data about malicious information objects on the Internet and providing their multi-aspect assessment and categorization using machine learning methods. The purpose of the investigation is to improve the efficiency of the detecting process of malicious information on the Internet using the examples of Web-pages classification.
About the Authors
A. .. Branitskiy
Saint-Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences
Russian Federation
Russian Federation
I. .. Saenko
Saint-Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences
Russian Federation
Russian Federation
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Review
For citations:
Branitskiy A..., Saenko I... The Technique of Multi-aspect Evaluation and Categorization of Malicious Information Objects on the Internet. Proceedings of Telecommunication Universities. 2019;5(3):58-65. (In Russ.) https://doi.org/10.31854/1813-324X-2019-5-3-58-65
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