An Auto-Upgradable End-to-End Preauthenticated Secure Communication Protocol for UAV-Aided Perception Intelligent System

Unmanned aerial vehicle (UAV)-enabled intelligent systems are emerging and empowering real-time monitoring and modeling tasks. The security requirements in real-time UAV-enabled intelligent systems are data integrity, authenticity, traceability, tamper-proofing, and privacy. A secure channel established by authenticated key agreement (AKA) protocol can cover all the security requirements. However, no UDP-based lightweight pairing-free AKA protocol has been proposed for the UAV system. In this article, we propose a UDP-compatible Curve25519-infrastructural identity-based end-to-end pre-AKA protocol (UDP-IBE2E-pAKA) with system auto-upgrading and direct and lifecycle credential revocation as a lightweight and reliable UDP-based secure communication module for UAV-enabled networks, which perfectly fits the rapid mobility and extremely harsh work environments of UAVs. To protect UAV-enabled systems stable from DDoS attacks, we construct an efficient identity-based signature as a preauthentication mechanism for the verifier to directly authenticate the sender without any redundant operations. In addition, to prevent the corrupted UAV from monitoring and disrupting attacks, our protocol can revoke the malicious entities directly and immediately with a revocation list in the authentication phase. Moreover, online mode auto-upgradable algorithms are designed to achieve key exposure resistance in our protocol. The full proof of the authenticity and privacy are given in this article. The comprehensive comparison with other state-of-the-art end-to-end AKA protocols indicates that our protocol meets the most robustness and highest efficiency on Raspberry Pi 5.

I. Introduction

With the high-maneuvering capability and mobility, unmanned aerial vehicles (UAVs) have attracted a lot of attention from academia and industry. UAVs can be flexibly deployed anywhere to provide fast intelligent condition-perception for different applications, e.g., environment monitoring [1], emergency rescue and disaster relief [2], and electronic reconnaissance [3]. The UAV-aided perception intelligent system has been enabled for various real-time computing modeling tasks (e.g., real-time battlefield 3-D modeling and real-time disaster 3-D modeling), which is composed of UAV clusters, information collection edge nodes, ground base stations, and fusion computing center. Fig. 1 shows a UAV-aided perception intelligence system. The UAV cluster is responsible for collecting real-time data. The edge node communicates directly with the UAV through the wireless network, which is responsible for data collecting and analyzing of the UAV cluster in close range; All UAV clusters communicate with the fusion computing center through the nearby ground base station. The information fusion computing center gathers the data transmitted from all UAV groups for global data analysis and real-time modeling. Fig. 1.

Generic model of UAV-aided perception intelligent system.