Design a sturdy and secure authentication scheme capable of early detection of COVID-19 patients using WBANs

Abdulla J. Y. Aldarwish, Ali A. Yassin, Abdullah Mohammed Rashid, Hamid Ali Abed Alasadi, Aqeel Adel Yaseen, Eman Thabet Khalid

Abstract


COVID-19 was first reported in China Wuhan and rapidly grown up to more than 58 countries based on the World Health Organization (WHO). Well ahead of any health emergency, the health care server has the ability to access these data via authorization and then s/he performs necessary actions. In order to protect medical data from malicious activities, authentication is the starting point for this. Authentication systems represent a network support factor to reduce ineffective users and radically eliminate phishing because authentication determines the identity of the real user. Many schemes and technologies have been suggested for authentication in wireless body area networks (WBANs). In this paper, we suggest a strong dynamic password authentication system for WBANs. We adopt a (different/new) way to calculate a password and make it coherent and dynamic for each login session. Our work also provides additional security properties to get rid of hub node impersonation attacks and resolve key escrow issues. Our scheme resist fishing attach which keep patient from any illegal change of drugs. By comparison, the proposed scheme is considered active and has strong security based on formal security analysis tools such as AVISPA.


Keywords


Authentication; AVISPA; COVID-19; Health care; Wireless body area networks;

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v27.i2.pp900-910

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics