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The area of digital technologies is currently the subject of many cyber threats, the frequency of which is increasing. One of the areas of cyber security is also the creation of models and estimates of the process of cyber threats and their possible financial impacts. However, some studies show that cyber-threat assessment to identify potential financial impacts for organizations is a very challenging process. A relatively large problem here is the detection of scenarios of cyber threats and their expression in time. This paper focuses on the design of an algorithm that can be applied to the field of cyber-threat assessment in order to express the financial impacts. The study is based on an in-depth analysis of the insurance industry. The results obtained in our research show the importance of the time perspective for determining the potential financial impacts of cyber threats for the field of insurance.

This article is focused on the creation of a data model of an information system to support the processes of population sheltering (PoS). PoS processes have undergone significant changes in the Czech Republic. The PoS system was transformed for the use of improvised shelters. For sustainable PoS, it is necessary to standardize the approach of crisis management staff. Key research hypotheses: the data model must respect the methodological framework of planning and implementation of the PoS, especially when used for the design and implementation of the improvised shelters; the standardization of residential buildings can be used to facilitate and streamline the sustainable process of planning of the PoS; the unified data model of the PoS can be considered suitable for standardization and development in the field of sustainable planning and implementation of the PoS. Softwares such as SW QGIS desktop 2.6.0, OpenStreetMap (OSM) spatial database, ESRI shapefile format, and S-JTSK/Krovak East North 5514 coordinate system were used for the verification of the spatial data model, and ASP.NET MVC 4.7.2 Microsoft SQL Server Express 2019, jQuery 3.3.1, Boot-strap 3.4.1, Kendo UI 2019.1.220, and virtual Windows Server 2016 were used for the implementation of the physical data model. The physical data model substantiates the benefits. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.