Comprehensive Security Model for Medical IoT: Hybrid Encryption and User Authentication for Data Protection
Safeguarding information in the M-IoT with a hybrid encryption scheme. Safeguarding private health information communicated across IoT networks while minimising computational strain and ensuring information reuse is an issue that this paradigm solves. Safe and secure data exchange between patients and medical professionals is made possible by the suggested design in situations that are both routine and emergency. An effective authentication method that reduces computing cost throughout encryption and decryption is offered by this hybrid technique, which combines symmetric security with encryption based on attributes (ABE). Additionally, the approach prevents pretending to be another man-in-the-middle, and replay assaults while ensuring the safety and security of data. The design incorporates healthcare officials overseeing security standards, encryption storage of information in the cloud, as well as node sensors that track patients’ vitals. If you’re looking for a solution for safe, large-scale M-IoT the deployments, look no farther than the hybrid approach. It beats out previous alternatives in terms of computing expenses, protection level, and encryption and decryption time. According to this chapter’s findings, the suggested paradigm improves medical IoT settings in terms of stability, safety, and user access management. When compared with Sirius and Plutus, the hybrid encryption model designed to secure medical data in the (M-IoT) outperforms them with regard to of efficiency & overall accuracy by over 97%.
Authors
- K Venkadeshwaran
- Manas Kumar Mallick (ORCID: https://orcid.org/0000-0002-4636-3611)
- Veena S Badiger (ORCID: https://orcid.org/0009-0005-9080-7004)
- Pavas Saini
- Lakshya Swarup (ORCID: https://orcid.org/0009-0006-3351-5248)
- M. Kulanthaivel
Institutions
- Jain University (IN)
- Presidency University (IN)
- Siksha O Anusandhan University (IN)
- Karpagam Academy of Higher Education (IN)
- Chitkara University (IN)
Publication Details
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1109/mpseciceta64837.2025.11118458
- Primary Topic
- Cloud Data Security Solutions
- Type
- article
- Field-Weighted Citation Impact
- 0.00