A Secure Authenticated Healthcare Data Analysis Mechanism in IoMT‐Enabled Healthcare
ABSTRACT We frequently wait long when we go to the hospital for a doctor's appointment. However, many people cannot afford to stay in such lengthy lines in today's busy world. Daily, we observe that manually performing such tasks takes considerable time, and automating such processes can save time. Securing the information the user provides, medical staff, and devices is crucial. Before accessing such information, the user must be authenticated to ensure that unauthorized persons cannot retrieve patient records. Internet‐of‐Things (IoT) has revolutionized the healthcare industry with the emergence of IoT‐based healthcare systems, called Internet‐of‐Medical‐Things (IoMT). It offers efficient and personalized patient care. However, the vast amounts of sensitive patient data transmitted and stored within these systems raise serious concerns about data security and privacy. This article proposes a secure healthcare data analysis mechanism with user sign‐in authentication capability for the IoMT‐enabled healthcare system (SA‐IoMTH). It addresses the unique security challenges faced by these systems. The formal security verification using the scyther tool and a security analysis of SA‐IoMTH are provided, proving its security against various possible attacks. The proposed SA‐IoMTH outperforms the other existing approaches. Finally, a smartphone application is also implemented for SA‐IoMTH to check its usefulness in real‐world scenarios.
Authors
- Mohammad Wazid (ORCID: https://orcid.org/0000-0001-9898-0921)
- Ashok Kumar Das (ORCID: https://orcid.org/0000-0002-5196-9589)
- Sachin Shetty (ORCID: https://orcid.org/0000-0002-8789-0610)
- SK Hafizul Islam (ORCID: https://orcid.org/0000-0002-2703-0213)
- Shivansh Nautiyal
Institutions
- Korea University (KR)
- Indian Institute of Information Technology Allahabad (IN)
- Graphic Era University (IN)
- International Institute of Information Technology, Hyderabad (IN)
- University of Kalyani (IN)
- Old Dominion University (US)
Publication Details
- Journal
- Security and Privacy
- Published
- 2024-09-26
- DOI
- https://doi.org/10.1002/spy2.468
- Citations
- 4
- Primary Topic
- User Authentication and Security Systems
- Type
- article
- Field-Weighted Citation Impact
- 3.12