Fuzzy-based Cybersecurity Risk Analysis of the Human Factor from the Perspective of Classified Information Leakage
| Autor: | Daniel Vaczi, Tamás Szádeczky, Edit Toth-Laufer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Risk analysis
Computer science Digital transformation Computer security computer.software_genre 030226 pharmacology & pharmacy Critical infrastructure Classified information 03 medical and health sciences 0302 clinical medicine Risk analysis (engineering) Workforce Information leakage Leakage (economics) Adaptation (computer science) computer |
| Zdroj: | SISY |
| DOI: | 10.1109/sisy50555.2020.9217053 |
| Popis: | Nowadays, the digital transformation of organizations is not a challenge but a must-have. In the spring of 2020, practically the whole world worked from home offices. Now digital adaptation is the challenge for many people and orgaization. This situation poses challenges for the cybersecurity world. At the time of writing this article, there is no exact data yet on what cybersecurity incidents have occurred or how much damage they have caused. Nevertheless, it is certain that in the pandemic chaos, many corporates made mistakes during their digital adaptation processes. To a considerable extent, these mistakes are due to humans. Even though there are outstanding technological solutions or regulations at a company, if this riskfactor is not appropriately managed, then the other two are worthless. Despite the need, there is no widespread human risk anylisys method in cybersecurity, because it is difficult to measure, and covered in obscurity. In this paper, the authors propose a fuzzy model to organizations whereby they can measure this risk if they have sufficient information about the workforce. The model will be easier understood if presented through a specific threat, the digital leakage of classified information from a critical infrastructure. |
| Databáze: | OpenAIRE |
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