Model of assessment of the security of information and communication systems based on fuzzy visions

Abstract

The current stage of development of information and communication systems is characterized by their massive advances in all spheres of everyday life: military law, government, economics, finance, industry, etc. The advancement of digital technologies will ensure the efficiency and speed of data processing, while simultaneously increasing the risk of threats to information security in the cyberspace. The task of assessing the threat or the security of information and communication systems based on known intelligence is important for several reasons. First of all, it allows you to go from a clear description of the risks to comprehensive estimates, which creates a basis for an economical solution. In another way, the analysis of traffic jams allows you to identify priority threats and optimize defense resources, focusing on the most critical scenarios. Thirdly, it reveals the possibility of using current mathematical methods for modeling non-significance in the field of information security. Classic methods for assessing the security of information and communication systems are based on the collection of clear statistical data about the threats and attacks. However, in practice, information about the severity of attacks and the scale of traffic attacks is often inconsistent, overly sensitive, or presented in what appears to be linguistic categories (“high risk of threat”, “significant losses”). In such minds, traditional methods demonstrate limited effectiveness due to the low accuracy of such assessments. This necessitates the need to create assessment systems that effectively deal with fuzzy information and establish cause-and-effect relationships between threats and potential losses. The article proposes a model for assessing the security of information and communication systems through potential losses based on type II fuzzy relations. A special feature of the model is the ability to deal with types of non-significance in a comprehensive manner. Fuzzy terms of threats and losses are formalized by interval functions of type II reliability, as a result of which the world significance of threats and losses is determined at intervals. The type II fuzzy model will be based on the extended compositional rule of Zadeh's derivation, from which two systems of fuzzy relations are combined. These systems link the lower (upper) boundaries of fuzzy relationships and the lower (upper) boundaries of the world of significance of threats and losses. The value of the output variable is determined by type reduction and defuzzification operations.