Homomorphic Encryption for Privacy-Preserving Misbehavior Detection in the Internet of Vehicles

Homomorphic Encryption for Privacy-Preserving Misbehavior Detection in the Internet of Vehicles

연구 분야: Cryptography

학회: 2025 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

Intelligent transportation systems (ITS) are vital in improving road safety, efficiency, and user experience. However, vehicular networks face critical security and privacy challenges due to the constant exchange of sensitive data. This paper proposes a robust, privacy-preserving framework for vehicular networks using homomorphic encryption, which enables secure computations on encrypted data while maintaining data confidentiality. The framework leverages the Cheon-Kim-Kim-Song (CKKS) homomorphic encryption scheme, enhanced by dynamic precision scaling to optimize security and computational efficiency. Comparative analysis across various key sizes demonstrates that the proposed framework effectively reduces computational, encryption, and decryption overheads while safeguarding data privacy.