BSP-IoD: A Secure Drone-Enabled Authentication Protocol Using Barrel-Shifter PUF
Due to the rapid proliferation of Unmanned Aerial Vehicles (UAVs), also termed as drones, the Internet of Drones (IoD) has revolutionized various domains including disaster response, smart surveillance, remote sensing, by facilitating real time collection of aerial data using autonomous coordination. However, the exposed communication landscape of IoD networks render them highly susceptible to known threats including forgery, impersonation and physical capture threats. Most of the conventional key agreement techniques are costly for computations and not suitable for resource constrained IoD system which necessitate low cost yet secure authentication mechanisms. Though, many lightweight drone authentication schemes have been presented, however with security limitations. This study suggested a novel Barrel-Shifter Physically Unclonable Function (BS-PUF) based drone authentication protocol (BSP-IoD) to augment security of IoD network. Leveraging the intrinsic randomness, commutative and invertible properties of BS-PUF, the BSP-IoD ensures construction of mutually agreed session key employing unique challenge-response pairs (CRPs). The scheme could withstand known threats besides supporting perfect forward secrecy and privacy to the user. The BSP-IoD considerably mitigates computational overheads besides ensuring resilience against known attacks including resistance from drone physical capture threat, promoting viability for next generation IoD networks. The formal analysis and performance assessment exhibit that BSP-IoD could address the critical challenges of next generation IoD applications. Furthermore, it supports 56.6% more number of security properties as compared to preceding schemes.
Authors
- Ashok Kumar Das (ORCID: https://orcid.org/0000-0002-5196-9589)
- Abdul Jaleel (ORCID: https://orcid.org/0000-0003-2536-9093)
- Azeem Irshad (ORCID: https://orcid.org/0000-0002-1366-2834)
- Ghulam Ali Mallah (ORCID: https://orcid.org/0000-0003-3428-9802)
- Shehzad Ashraf Chaudhry (ORCID: https://orcid.org/0000-0002-9321-6956)
- Abid Mehmood (ORCID: https://orcid.org/0000-0002-1468-7259)
Institutions
- Abu Dhabi University (AE)
- University of Wah (PK)
- Pakistan Army (PK)
- Charles Darwin University (AU)
- Shah Abdul Latif University (PK)
- International Institute of Information Technology, Hyderabad (IN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1109/jiot.2025.3615297
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00