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Position Papers of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 31

A Comparative Study of User Identification for COVID-19 Vaccination Online Registration

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DOI: http://dx.doi.org/10.15439/2022F272

Citation: Position Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 31, pages 8993 ()

Full text

Abstract. Due to the COVID-19 pandemic, individuals have been encouraged to obtain COVID-19 vaccinations. As part of the vaccination process, it is necessary to verify the identity before obtaining the vaccines. Incorrectly identifying the individuals could lead to serious consequences. For example, an incorrect vaccination schedule ( e.g., incorrect timing between doses and incompatible brands) may cause undesired side effects to an individual, so it should be more accurate and convenient to identify themselves whenever and wherever people are required. One of the most effective and commonly used identification methods is face-to-face (or offline) identification. However, the method is typically time-consuming and is not suitable for the current situation where individuals should avoid direct contact. Hence, there is a growing trend for an online identification method where individuals use digital credentials to identify themselves. This paper suggests an online authentication system for improvements by investigating how different people authenticate themselves online in each country for COVID-19 vaccination. Comparing the online authentication systems between a country that have their national identification cards or not makes the Pros and Cons of both systems clear, particularly, in Japan and Thailand.


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