STUDY OF THE TRAFFIC ENCODING METHOD IN SECURE INFORMATION TRANSMISSION CHANNELS

Abstract

In the era of global informatization, social networks are of great importance for obtaining various information by network users. But it must be taken into account that social networks such as Facebook, Twitter, instagram contain billions of raw unstructured data, the processing of which is indeed quite a difficult task to study. Data mining allows you to extract current information from a large number of data sets, structure and, after the analysis, gain knowledge by detecting patterns between data, which makes it possible to predict changes in the network that have occurred based on the interactions of information flows and events. This information is used in various fields such as business, education, medicine, cyber security, etc. The field of data mining has made huge strides from its inception to its current level, but Data Mining continues to face many challenges, especially when processing social media data. This article is devoted to the analysis of various data mining methods that are used for social network analysis, as well as the study of the most priority areas in the field of data mining based on the review of various studies, and also focuses on the field of data mining in social networks, which will be used in further research.