Lightweight Drone-to-Ground Station and Drone-to-Drone Authentication Scheme for Internet of Drones

The implementation of the Authentication and Key Agreement (AKA) protocol in the Internet of Drones (IoD) is crucial for enhancing the security and reliability of information transmission. However, almost all existing authentication protocols between drones and Ground Station (GS) may suffer from several attacks due to capture attacks. In addition, the authentication between drones requires the participation of GS, which not only increases the amount of computation and transmission but also faces challenges such as impersonation attacks, lack of privacy protection, and perfect forward security. Therefore, we propose a secure and lightweight drone-to-GS (D2G) and D2D AKA protocol with perfect forward secrecy for IoD. Our protocol integrates physical unclonable functions (PUF) symmetrically into GS and drones to protect secret information against capture attacks while ensuring that GS does not store secret information related to drones. Furthermore, the proposed protocol enables direct mutual authentication between drones in a symmetrical manner without GS involvement, improving security and efficiency, particularly in scenarios where drones must collaborate without GS connectivity. Formal security proof using the random oracle model confirms the protocol’s resilience against various attacks. The performance analysis indicates that our scheme improves computational efficiency by an average of 39.44% compared to existing schemes that offer comparable security. Additionally, our approach incurs zero storage overhead during the GS authentication process. This protocol offers a secure and efficient solution for IoD, enhancing both security and scalability.

Authors

Institutions

Publication Details

Journal
Symmetry
Published
2025-04-05
DOI
https://doi.org/10.3390/sym17040556
Citations
3
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
14.98

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Lightweight Drone-to-Ground Station and Drone-to-Drone Authentication Scheme for Internet of Drones

Qi Xie, Jilin Zhang
3 citations
Symmetry
UAV Applications and Optimization
14.98
article

Lightweight Drone-to-Ground Station and Drone-to-Drone Authentication Scheme for Internet of Drones

Qi Xie, Jilin Zhang
article en
3 citations

Abstract

The implementation of the Authentication and Key Agreement (AKA) protocol in the Internet of Drones (IoD) is crucial for enhancing the security and reliability of information transmission. However, almost all existing authentication protocols between drones and Ground Station (GS) may suffer from several attacks due to capture attacks. In addition, the authentication between drones requires the participation of GS, which not only increases the amount of computation and transmission but also faces challenges such as impersonation attacks, lack of privacy protection, and perfect forward security. Therefore, we propose a secure and lightweight drone-to-GS (D2G) and D2D AKA protocol with perfect forward secrecy for IoD. Our protocol integrates physical unclonable functions (PUF) symmetrically into GS and drones to protect secret information against capture attacks while ensuring that GS does not store secret information related to drones. Furthermore, the proposed protocol enables direct mutual authentication between drones in a symmetrical manner without GS involvement, improving security and efficiency, particularly in scenarios where drones must collaborate without GS connectivity. Formal security proof using the random oracle model confirms the protocol’s resilience against various attacks. The performance analysis indicates that our scheme improves computational efficiency by an average of 39.44% compared to existing schemes that offer comparable security. Additionally, our approach incurs zero storage overhead during the GS authentication process. This protocol offers a secure and efficient solution for IoD, enhancing both security and scalability.

SymmetryVol. 17(4)
Hangzhou Normal University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 2%
UAV Applications and Optimization
14.98
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.