Security Vulnerability Analysis and Enhancement of a Lightweight Sensor Node Authentication Framework

This study presents a comprehensive structural and mathematical security analysis of LightAuth, a lightweight authentication framework, specifically designed for smart health sensor networks. We delve into its core components and identify several critical vulnerabilities that could compromise the integrity and security of the system. Our analysis reveals that the framework suffers from insufficient freshness verification, a flawed and biased key agreement process, and the persistent exposure of fixed identifiers, which makes it susceptible to various attacks. To address these significant security weaknesses, we propose a suite of practical and effective countermeasures. These enhancements include the implementation of a robust timestamp+nonce validation mechanism to ensure message freshness and the introduction of mutual signature verification to prevent man-in-the-middle attacks. Furthermore, we advocate for the use of dynamic pseudonyms to obfuscate user identities and enhance privacy. To bolster long-term security, we also integrate perfect forward secrecy (PFS), which ensures that a compromise of a long-term key does not compromise past session keys. We conducted extensive simulations to evaluate the effectiveness of these proposed enhancements. The results demonstrate that our improvements achieve a remarkable 100% replay detection rate, while the performance degradation remains within acceptable limits, proving the practicality of our solution.

@article{Yee2025,
  title     = {Security Vulnerability Analysis and Enhancement of a Lightweight Sensor Node Authentication Framework},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {11},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Kim Kyoung Yee and Haewon Byeon},
  doi       = {10.14569/IJACSA.2025.0161112},
  url       = {https://doi.org/10.14569/IJACSA.2025.0161112}
}