Journal article icon

Journal article : Review

Advancing IoT-driven transportation security: a comprehensive review of privacy-preserving identity-based encryption with quantum enhancements

Abstract:
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.
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Publisher copy:
10.1109/ojits.2026.3651438

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


More from this funder
Funder identifier:
https://ror.org/013aysd81
Grant:
RS-2024-00340882


Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Open Journal of Intelligent Transportation Systems More from this journal
Volume:
7
Pages:
268-284
Publication date:
2026-01-06
Acceptance date:
2025-12-28
DOI:
EISSN:
2687-7813


Language:
English
Keywords:
Subtype:
Review
Pubs id:
2358660
Local pid:
pubs:2358660
Source identifiers:
W7118780191
Deposit date:
2026-04-29
ARK identifier:

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP