Abstract
In today's information world, the use of VoIP has become an attractive option for user communication. With the downward trend in paying for basic broadband services and the rapid increase in internet speeds, the use of VoIP should only continue to grow in popularity. However, as the use of VoIP increases, so do the potential threats to ordinary users. This article examines the peculiarities of organizing corporate VoIP telephony systems, highlights the main problems in information protection systems in VoIP telephony, and outlines ways to solve them. The development of methods for speech analysis and corresponding processing of natural language, which allows for creating more accurate and effective systems for detecting anomalous traffic and potentially dangerous communications, is especially relevant. With the continuous development of artificial intelligence technologies, the direction of using intelligent means for content analysis in the VoIP system is becoming interesting. A method for detecting anomalies in IP-telephony traffic, based on grouping VoIP messages through context-frequency analysis, is proposed. Additionally, a method for automated filling of the ontology of thematic messages in corporate IP-telephony systems is proposed, based on the formalized presentation of messages using tree-like structures and the description of interaction operations through tuple algebra. Furthermore, a software implementation for converting voice messages into text representations using the SpeechRecognition library for voice-to-text conversion in the Python programming language was created. Experimental studies of the proposed approaches were conducted, and a software subsystem for detecting anomalous messages based on the ontological approach was implemented in the current corporate IP-telephony system.
Published Version
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