DCASR: Distributed Collaborative Authentication With Specified Security Strength and Resource Optimization Selection in AAV Networks

Xinyi Zhao, Yunwei Wang, Xinghua Li, Yinbin Miao, Robert H. Deng

Abstract: Collaborative authentication, boasting-enhanced accuracy, robust resilience, and optimized efficiency, holds immense promise for autonomous aerial vehicle (AAV) networks. However, existing collaborative authentication methods overlook both the credibility evaluation and incentives of participating nodes, thereby compromising authentication accuracy and resulting in failures. Furthermore, reliance on trusted decision-fusion institution introduces vulnerabilities and single points of failure. To address these issues, we design a credibility-weighted soft authentication approach specifically for AAV networks, thereby enhancing accuracy by effectively integrating the trustworthiness of collaborating nodes. To further encourage active participation from nodes, we introduce an incentive-based reputation system. Finally, based on the above approaches, we propose a distributed authentication method by leveraging blockchain technology and optimization theory that not only emphasizes security but also optimizes resource selection in AAV networks. Theoretical analysis demonstrates our scheme’s distributed authentication with minimized resource consumption under specified security strength, mitigating single points of failure and fulfilling efficient mutual authentication requirements. Experimental results show a remarkable 78.45% increase in authentication accuracy and a 44.51% reduction in resource consumption compared to advanced solution.

External IDs:dblp:journals/iotj/ZhaoWLMD25