METHODS AND ALGORITHMS FOR DETECTING POTENTIAL VIRUSES AND EXPLOITS IN TEXT FEEDBACK DATA

Rusakov Aleksej Mixajlovich, Amelyutin Evgenij Vyacheslavovich, Rudkov Yaroslav Igorevich

The paper describes one of the possible approaches to identifying potential viruses and exploits in text feedback data. Timely detection of traces and descriptions of viruses and exploits in text feedback data contributes to an increase in the overall level of security. The paper presents an approach for detecting cyber threats by the method of intelligent text analysis, capable of working on big data in order to identify attacks that can be implemented in the form of Internet links, polymorphic malware and Trojan cryptographers engaged in extortion.

Keywords:text mining, information security, detection exploits in the text, feedback.