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Journal Article
PSL-AKA: Physically Secure and Lightweight Authenticated Key Agreement Protocol for Wearable Devices
- Authors
- Joohyun Kim, Daewon Kim, Kisung Park
- Issue Date
- 2025-12
- Citation
- IEEE Access, v.13, pp.206138-206154
- ISSN
- 2169-3536
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Abstract
- Wearable devices such as smartwatches and fitness trackers are widely used for healthcare monitoring but face limitations in storage and computational capacity. To handle resource-intensive tasks, many operations are outsourced to servers, which requires transmitting sensitive information through public networks. This reliance on external servers creates security challenges, exposing data to potential interception and manipulation. Although various authentication and key agreement (AKA) protocols have been proposed to mitigate these risks, a significant number still remain exposed to physical capture attacks (PCA). Such vulnerabilities undermine both data confidentiality and the establishment of mutual authentication. In this paper, we propose a physically secure and lightweight authenticated key agreement (PSL-AKA) protocol for wearable devices. PSL-AKA employs physical unclonable function (PUF) technology to strengthen protection against PCA while supporting efficient storage and reliable authentication. The protocol establishes secure session keys between wearable devices and cloud servers, ensuring confidentiality, integrity, and mutual authentication under insecure conditions. Security robustness is also verified through the Real-or-Random (ROR) model and the AVISPA tool. Performance evaluation shows that PSL-AKA achieves lower computational cost and reduced communication overhead compared with existing AKA schemes. These results demonstrate that PSL-AKA offers a practical and secure solution for protecting wearable devices in healthcare and IoT environments.
- KSP Keywords
- AVISPA tool, Authenticated key agreement protocol, Capture attacks, Cloud server, Communication overhead, Computational capacity, Fitness Trackers, Healthcare Monitoring, IoT environment, Performance evaluation, Resource-intensive
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
(CC BY NC ND)
