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Smart city energy efficient data privacy preservation protocol based on biometrics and fuzzy commitment scheme
- Source :
- Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
- Publication Year :
- 2024
- Publisher :
- Nature Portfolio, 2024.
-
Abstract
- Abstract Advancements in cloud computing, flying ad-hoc networks, wireless sensor networks, artificial intelligence, big data, 5th generation mobile network and internet of things have led to the development of smart cities. Owing to their massive interconnectedness, high volumes of data are collected and exchanged over the public internet. Therefore, the exchanged messages are susceptible to numerous security and privacy threats across these open public channels. Although many security techniques have been designed to address this issue, most of them are still vulnerable to attacks while some deploy computationally extensive cryptographic operations such as bilinear pairings and blockchain. In this paper, we leverage on biometrics, error correction codes and fuzzy commitment schemes to develop a secure and energy efficient authentication scheme for the smart cities. This is informed by the fact that biometric data is cumbersome to reproduce and hence attacks such as side-channeling are thwarted. We formally analyze the security of our protocol using the Burrows–Abadi–Needham logic logic, which shows that our scheme achieves strong mutual authentication among the communicating entities. The semantic analysis of our protocol shows that it mitigates attacks such as de-synchronization, eavesdropping, session hijacking, forgery and side-channeling. In addition, its formal security analysis demonstrates that it is secure under the Canetti and Krawczyk attack model. In terms of performance, our scheme is shown to reduce the computation overheads by 20.7% and hence is the most efficient among the state-of-the-art protocols.
- Subjects :
- Authentication
Biometrics
Fuzzy commitment
Security
Privacy
Efficiency
Medicine
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 14
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9aff3fba431d4fbd8c28769fbf8d9ac6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41598-024-67064-z