METHODS OF NATURAL LANGUAGE ANALYSIS USING NEURAL NETWORKS IN CYBER SECURITY

The work emphasizes the relevance of natural language processing (NLP) in the modern world, in particular due to the constant growth of text data in social networks, e-commerce and online media. The authors note that the effective processing of such data is critically important for business and public administration, as it allows generating new knowledge, predicting trends and making informed decisions. NLP also makes a significant contribution to improving the efficiency of organizations by automating the processing of text information (for example, in customer support systems and feedback analysis). In addition, the article emphasizes the significant prospects for the application of NLP in the field of cybersecurity. In particular, NLP is used for automatic anomaly detection, network traffic monitoring and detection of phishing attacks. For such tasks, deep models (for example, RNN, LSTM, CNN) are used, as well as the latest transformer architectures that are capable of processing large amounts of information in real time. The work also raises important questions related to the challenges of modern NLP, including the need for large computational resources, multilingualism, model