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Privacy-preserving adaptive traffic signal control in a connected vehicle environment
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“A traffic signal control framework for connected autonomous vehicles (CAV) was proposed in [135]. The framework integrates SMPC and DP to protect CAV data against three types of privacy threats: collusion attacks, control center database attacks, and inference attacks.”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [135]
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“The framework used a linear programming model and arrival rate estimator to ensure efficiency in varying traffic scenarios. A two-stage stochastic programming model mitigates DP-induced noise impacts on performance.”
From Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction (2025) · cites this paper as [135]
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Cites
Privacy-preserving data publishing: A survey of recent developments
Fung, B. C. M., Wang, K., Chen, R., & Yu, P. S. (2010) · ACM Computing Surveys · doi:10.1145/1749603.1749605 · Cited by 1,704 · cited 1×
“…to protect against inference attacks, i.e., the limitations of most traditional mechanisms (e.g., anonymization-and aggregation-based mechanisms) in which an adversary may obtain private information by analyzing the changes in the query results, possibly with the help of external datasets [39].”
BackgroundSecure Multi-Party Computation: Theory, practice and applications
Zhao, C., Zhao, S., Zhao, M., Chen, Z., Gao, C.-Z., Li, H., & Tan, Y.-A. (2019) · Information Sciences · doi:10.1016/j.ins.2018.10.024 · Cited by 508
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Cited by
Sorted by citations
Islam, N., & Zulkernine, M. (2025) · arXiv · doi:10.48550/arxiv.2503.01089 · Cited by 9
“Two popular aggregation algorithms are federated averaging (FedAvg) and federated distillation [12].”
Metadata
- Authors
- Tan, C., & Yang, K.
- Affiliations
- National University of Singapore (SG)
- Corresponding author
- Yang, Kaidi
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2024-01
- Volume
- 158
- Pages
- 104453
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W4389636506
- Cited by
- 49
- References
- 2
- Citations by year
- 2026: 11 · 2025: 26 · 2024: 11
- FWCI
- 5.26
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Transportation Research Part C Emerging Technologies (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Funders
- Ministry of Education - Singapore (A-8000404-01-00)
- National University of Singapore
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Transportation › Transportation Planning and Optimization
- Keywords
- connected vehicles, secure multi-party computation, differential privacy, collusion attacks, inference attacks, database attacks, traffic signal optimization, arrival rate estimation, stochastic programming, queue reduction, vehicle delay, privacy-utility trade-off
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