Method and Means of Critical Information Processing in Corporate Networks

The article studies modern methods and means of processing critical information in corporate networks. Since the growth of data volumes increases the risk of data breaches, the main causes of such incidents are analyzed, in particular, unintentional personnel errors (misdelivery, misconfiguration) and abuse of privileges by insiders. Data Loss Prevention (DLP) technologies are considered as a key mechanism for data protection, including detection, monitoring, prevention and audit of information flows. A comparative analysis of different models of DLP systems (centralized, distributed, hybrid) and their application in the corporate environment has been carried out. Particular attention is paid to commercial solutions from leading manufacturers, their capabilities, advantages and disadvantages. The article focuses on the current challenges of DLP systems, such as the high frequency of false positives, limited capabilities for analyzing encrypted traffic, difficulties in detecting insider threats, and scalability issues. A review of recent research demonstrates promising approaches combining anomaly analysis, machine learning, attribute-based encryption (CP-ABE), and Zero Trust principles. The article discusses the peculiarities of using botnets to steal critical information in corporate networks. A solution for protecting information in case of botnet activity is proposed, based on the integration of data leakage prevention systems (DLP) - a module specially configured to neutralize botnet threats. The results of the study indicate the need for an integrated approach to information security, which includes a combination of technological, organizational and legal measures. This will significantly reduce the risks of data leakage and ensure reliable protection of critical information in the face of modern cyber threats.