Efficient Chaotic Block Encryption Scheme for Secure Communication in <scp>CR</scp>‐<scp>VANET</scp> Through a Riemannian Residual Neural Network With Narwhal Optimization
ABSTRACT Cognitive radio vehicular ad hoc networks (CR‐VANETs) play a vital role in intelligent transportation systems by enabling dynamic communication between vehicles and infrastructure. However, ensuring secure and efficient data transfer in these networks is challenging due to the high computational complexity, vulnerability to attacks, and inability of conventional encryption methods to adapt to dynamic network configurations. These limitations compromise the reliability and security of vehicular communications. To overcome these challenges, we propose the efficient chaotic block encryption scheme for secure communication in CR‐VANET through a Riemannian residual neural network with narwhal optimization (R2Net_NO+CBC). This novel approach enhances encryption flexibility, addressing CR‐VANETs' dynamic nature by integrating chaos‐based encryption, deep learning, and optimization techniques. By improving security while maintaining computational efficiency, our method offers a robust solution for safeguarding vehicular communications in next‐generation transportation networks. The research focuses on secure communication in CR‐VANETs, specifically addressing message encryption for privacy using chaotic block cipher (CBC) to prevent eavesdropping and unauthorized access. The proposed R2Net_NO+CBC scheme ensures robust security even in the worst connection environments while maintaining low computational overhead, enabling higher throughput and faster response times to counteract signal degradation without compromising security. Our solution outperforms existing methodologies, achieving a performance ratio exceeding 92% in encryption, computational speed, and system recovery time. Overall, this approach effectively addresses the challenge of establishing a secure and efficient communication network for CR‐VANETs, offering superior security and efficiency beyond what traditional encryption methods can provide.
Authors
- N. Pandeeswari
- Deepika Arunachalavel
Institutions
- SRM Institute of Science and Technology (IN)
- Social Service Sericulture Project Trust (IN)
Publication Details
- Journal
- Transactions on Emerging Telecommunications Technologies
- Published
- 2025-05-20
- DOI
- https://doi.org/10.1002/ett.70177
- Citations
- 1
- Primary Topic
- Chaos-based Image/Signal Encryption
- Type
- article
- Field-Weighted Citation Impact
- 1.28