Study of the issues of methods for determining the type of content in incoming traffic

Content filtering in the context of cybersecurity and trusted environments is an important tactic used to ensure network security and functionality. It works by restricting access to certain websites, emails, files or other content that may contain harmful elements or pose a significant risk of infection. Content filtering ensures the security not only of an individual user's data, but also of an entire network of organizations and institutions, helping to minimize the risk of malicious security breaches. The study of methods for determining the type of content in incoming traffic is a relevant and important area in the field of information security and network analytics. In today's Internet space, a significant amount of data is transmitted through networks, and one of the key tasks is the classification of this traffic to ensure security and effective network management. Methods for determining the type of content in incoming traffic are a set of algorithms and approaches that allow you to automatically determine what type of data is transmitted over the network. In the course of studying the problems of methods for determining the type of content in incoming traffic, data on network traffic is collected, a data set is selected for training the model, we consider classifier algorithms and focus on metrics for assessing classification efficiency. The results of the study can be used to create effective systems for detecting malicious or unwanted content, filtering data, or optimizing the operation of network resources. The study of methods for determining the type of content in incoming traffic is of practical importance and can be applied in various fields, including information security, network analytics, monitoring of network resources and optimization of network processes.