Analytical Review of Classification and Clustering Methods of Cyber Attacks Based on Data Mining and Neural Network Approach

Abstract

This article provides an overview and analysis of methods of classification and clustering of cyber attacks, as well as their advantages and disadvantages. The purpose of this work is to provide an overview of the methods of classification and clustering of cyber attacks and to analyze their effectiveness in various conditions. The article discusses the main problems associated with the classification and clustering of cyber attacks, such as data uncertainty and complexity of objects. The results of the analysis show that classification and clustering methods are important tools for detecting and preventing cyber attacks. However, in order to achieve the best results, it is necessary to take into account the specifics of each method and apply them according to specific conditions.