cyber security

This paper explores the use of diarization systems which employ advanced machine learning algorithms for the precise detection and separation of different speakers in audio recordings for the implementation of an intruder detection system. Several state-of-the-art diarization models including Nvidia’s NeMo, Pyannote and SpeechBrain are compared. The performance of these models is evaluated using typical metrics used for the diarization systems, such as diarization error rate (DER) and Jaccard error rate (JER).

In this article, the authors focused on analyzing the possibilities of using artificial intelligence models for effective detection and analysis of cybercrimes. A comprehensive method using artificial intelligence algorithms, such as Random Forest and Isolation Forest algorithms, is developed and described to detect ransomware, which is one of the main threats to information security management systems (ISMS) in the field of critical infrastructure.

It was emphasized that ensuring the safety of children is one of the priority tasks of the state. Today, in the conditions of rapid digital development, new challenges and threats to the well-being of children appear, which require the search for effective tools to overcome them and provide a comprehensive approach to ensuring the safety of children in cyberspace.

The most common problems faced by modern information and communication systems (ICS) in the context of combating cyber threats were examined in the paper. The importance of ensuring the reliable operation of ICS, and protecting their users' private data from unauthorized interception or destruction was emphasized. The main principles of effective protection of ICS systems against possible interference in their work were defined. The classification of cyber threats and their impact on the functioning of information systems was presented.

The article is devoted to the analysis of the current state and challenges in the field of cyber security in the banking sector of Ukraine. The work examines the key concepts and main aspects of cyber security in the context of the banking sector, especially because of the growing requirements for the protection of data and financial transactions in the digital space.

In recent years, many companies have begun to integrate artificial intelligence systems (AIS) into their infrastructures. AIS is used in sensitive areas of society, such as the judicial system, critical infrastructure, video surveillance, and others. This determines the need for a reliable assessment and guaranteed provision of cyber security of AIS. The study analyzed the state of affairs regarding the cyber security of these systems. Possible types of attacks are classified and the main ones are considered in detail.

      Based on analysis of the Tech Summer for Teachers Bootcamp webinars for the educational community organized by the IT Company SoftServe, attention is focused on their interdisciplinary approach, in particular in the teaching of philosophical disciplines. Special attention was paid to the anthropological component in the field of information technologies, artificial intelligence, cybersecurity and virtual communication.