CONSIDERATION OF MATHEMATICAL MODELS OF INTEGRITY RISK
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Abstract
This article provides an overview of mathematical models used to analyze the risk of violation of the integrity of video information. It discusses the main modeling methods, including statistical models, machine learning models, and probabilistic models focused on the specific features of video data. Both traditional and modern approaches to detecting and preventing violations of the integrity of video information, including image and video processing algorithms, steganography and content analysis methods, are discussed. Special attention is paid to the application of these models in various fields, such as video surveillance, multimedia systems, telecommunications and others. The article also discusses the advantages and limitations of various approaches to modeling the risk of violation of the integrity of video information and offers recommendations on choosing the most appropriate model depending on specific tasks and conditions. This review can be useful both for researchers involved in the field of video data security and for practitioners in the field of information security and video analytics.
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References
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