PHISHING DETECTION IN ELECTRONIC COMMUNICATION CHANNELS

The article is devoted to increasing the effectiveness of information protection tools in domestic cyberspace by automated detection of phishing in text messages of electronic communication channels. It is shown that phishing remains one of the dominant vectors of cyberattacks, in particular in conditions of active use of social engineering methods and psycho-emotional influence, which significantly complicates its timely detection by traditional signature and statistical methods. It is established that most of the known neural network solutions are characterized by high resource intensity, require the formation of significant volumes of marked-up training data and are insufficiently adapted to the specifics of domestic content, which is characterized by limited marked-up corpora, morphological variability and sensitivity to contextual social engineering influences. To overcome these limitations, the article proposes a method for detecting phishing, which is based on the use of proven dialogical intelligent assistants based on large language models in the mode of formalized dialogical interaction. The method involves automated analysis of text messages by submitting standardized qu