Preserving Location Privacy of IoT Devices in Heterogeneous Edge Computing Architecture Through Deniability-Based Authentication
Edge computing moves cloud services closer to consumer Internet of Things (IoT) devices, reducing latency and bandwidth usage. This setup enables faster responses but also introduces new security challenges, particularly concerning location privacy when sender and receiver use different security techniques. The authentication process in such architectures can expose the location of IoT devices. To address this issue, researchers have proposed various privacy-preserving schemes. However, these are computationally heavy for IoT devices. To tackle this issue, we propose two novel heterogeneous deniable authentication schemes: HDA-IoT-I and HDA-IoT-II. These schemes use public-key infrastructure and identity-based cryptography to protect the location privacy of IoT devices in heterogeneous edge computing environments. Our schemes enable the designated edge device to verify the source of a message without being able to prove its origin to a third party, thus preserving privacy. Additionally, they incorporate a batch verification method, which speeds up the verification of multiple deniable authenticators. The proposed schemes are formally proven secure in the random oracle model based on the hardness assumption of elliptic curve inverse computational Diffie-Hellman problem. The performance evaluation demonstrate that our schemes significantly enhance computational and communication efficiency, making them suitable for IoT devices.
Authors
- Ikram Ali (ORCID: https://orcid.org/0000-0002-1499-9594)
- Abdul Wakeel (ORCID: https://orcid.org/0000-0002-9746-6290)
- Jie Chen (ORCID: https://orcid.org/0000-0002-9811-1694)
- Yong Chen (ORCID: https://orcid.org/0000-0003-4580-8655)
- Jianqiang Li (ORCID: https://orcid.org/0000-0002-2208-962X)
- Shamsher Ullah
Institutions
- University of Electronic Science and Technology of China (CN)
- Shenzhen University (CN)
- National University of Sciences and Technology (PK)
Publication Details
- Journal
- IEEE Transactions on Consumer Electronics
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1109/tce.2025.3544271
- Citations
- 3
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 7.44
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province
- Science, Technology and Innovation Commission of Shenzhen Municipality