Author
Listed:
- Lordwin Cecil Prabhaker Micheal
(Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, Tamilnadu, India)
- Xavier Fernando
(Department of Electrical and Computer Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada)
- Mathan Kumar Arumugasamy
(Department of Artificial Intelligence and Data Science, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai 600062, Tamilnadu, India)
- Neelamegam Devarasu
(Department of Electronics & Communication Engineering, Indian Institute of Information Technology (IIIT), Senapati 795001, Manipur, India)
- Daisy Merina Rathinarajan
(Department of Artificial Intelligence and Data Science, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai 600062, Tamilnadu, India)
Abstract
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 ( 2 336 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.
Suggested Citation
Lordwin Cecil Prabhaker Micheal & Xavier Fernando & Mathan Kumar Arumugasamy & Neelamegam Devarasu & Daisy Merina Rathinarajan, 2026.
"SLEVA-AV: An Edge-Centric IoT Security Architecture Using Multi-Stage Lightweight Encryption for Autonomous Vehicle Applications,"
Future Internet, MDPI, vol. 18(5), pages 1-18, May.
Handle:
RePEc:gam:jftint:v:18:y:2026:i:5:p:245-:d:1935762
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