Advancing IoT-Driven Transportation Security: A Comprehensive Review of Privacy-Preserving Identity-Based Encryption With Quantum Enhancements

초록

Intelligent transportation initiatives increasingly employ extensive networks of Internet-of-Things (IoT) sensors in combination with fog-computing platforms that locate computational resources near data sources in both maritime and urban environments. Although such connectivity enhances traffic monitoring and control, it simultaneously broadens the attack surface, placing sensitive operational data at heightened risk. Identity-Based Encryption (IBE) simplifies cryptographic key management in these contexts; however, it remains constrained by key-escrow exposure and the practical complexity of securely distributing private keys. This study analyzes these limitations and evaluates the extent to which two quantum techniques, Blind Quantum Computation (BQC) and Quantum Annealing (QA), can provide effective solutions. In particular, BQC enables encrypted computation without disclosing the user's identity to the processing server, thereby substantially mitigating the key-escrow vulnerability inherent in conventional IBE deployments. Meanwhile, QA is recommended for its ability to dynamically optimize network performance and security configurations. By synthesizing recent developments, discussing challenges, and recommending quantum-enhanced solutions, this study marks a significant step towards securing and optimizing smart transportation systems through advanced cryptographic techniques and quantum computing.

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