Autonomous vehicle (AV) networks require secure and efficient data processing under strict latency and resource constraints. This paper proposes a secure, lightweight edge-centric framework, SLEVA-AV, for Internet of Things (IoT)-enabled autonomous vehicle communication. The framework integrates multi-modal sensor data processing, lightweight key management, multi-stage encryption, and integrity verification within a unified pipeline. A key derivation function (KDF) is employed to generate session keys using contextual parameters, enabling efficient re-keying during vehicular mobility without repeated handshake overhead. The encryption process combines PRESENT, SPECK, and lightweight encryption algorithm (LEA) ciphers to enhance cryptographic strength, while SHA-256 ensures data integrity. The proposed system is implemented using a CARLA-based simulation environment and validated through CrypTool 2-based cryptographic analysis. Performance evaluation over 10,000 samples demonstrates low latency (0.039–0.794 s), reduced energy consumption (0.0196–0.0589 J), and negligible key management overhead. Comparative analysis with recent state-of-the-art approaches shows improved scalability and efficiency. Security validation through attack simulations demonstrates resistance against brute-force (2336 key space), differential (2−185), replay, and tampering attacks, achieving 100% detection accuracy. The results indicate that the proposed framework strikes a balanced trade-off among security strength, computational efficiency, and real-time performance, and it is suitable for deployment in IoT environments with high mobility and dynamic edge connectivity.
Micheal et al. (Tue,) studied this question.