Title
A Scalable and Secure Group Key Management Method for Secure V2V Communication.
Abstract
Safety applications based on vehicle-to-everything (V2X) communications can significantly enhance road safety and reduce traffic fatalities. Ensuring the security and privacy of the vehicular network is essential for the widespread adoption of V2X communications for commercial use. V2X safety and service applications require periodic broadcast communications among all the vehicles. However, compared to unicast communication, it is extremely challenging to provide broadcast communication with network security requirements such as confidentiality, in infotainment contents distribution, sensor data sharing, and security credentials management services. To address the providing confidentiality of vehicle-to-vehicle (V2V) broadcasting, we propose a group key management and message encryption method that is secure, lightweight, and scalable. The proposed group key management method can efficiently handle various scenarios like a node joining or leaving the group, with scalable rekeying algorithms. It employs a distributed and scalable architecture that offers several advantages such as the reduction of the key management overhead and the enhancement of the security level by keeping the key sizes with large networks. In addition, the proposed method employs a lightweight matrix-based encryption algorithm that can be easily applicable with the proposed group key management method. Further, we have implemented the proposed method and evaluated the performance using a V2V network simulator with several networks of highly dynamic group members. The simulation results show that the proposed method can reduce computation time for group key generation and message encryption by more than 80% compared to existing methods.
Year
DOI
Venue
2020
10.3390/s20216137
SENSORS
Keywords
DocType
Volume
scalable group key management,secure group communication,vehicle-to-vehicle communication,matrix-based group key generation,group message encryption algorithm
Journal
20
Issue
ISSN
Citations 
21
1424-8220
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Hayotjon Aliev100.34
Hyungwon Kim23014.13
Sunghyun Choi33329348.07