MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems
文献类型：期刊论文
| 作者 | Liu, Mingming6; Cheng, Long5; Gu, Yingqi4; Wang, Ying3; Liu, Qingzhi2; O'Connor, Noel E.1,6 |
| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
 |
| 出版日期 | 2021-01-28 |
| 页码 | 7 |
| ISSN号 | 1524-9050 |
| 关键词 | Cost function Urban areas Real-time systems Roads Privacy Convergence Base stations Speed advisory systems multi-party computation vehicle networks optimal consensus algorithm |
| DOI | 10.1109/TITS.2021.3052840 |
| 英文摘要 | As a part of Advanced Driver Assistance Systems (ADASs), Consensus-based Speed Advisory Systems (CSAS) have been proposed to recommend a common speed to a group of vehicles for specific application purposes, such as emission control and energy management. With Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) technologies and advanced control theories in place, state-of-the-art CSAS can be designed to get an optimal speed in a privacy-preserving and decentralized manner. However, the current method only works for specific cost functions of vehicles, and its execution usually involves many algorithm iterations leading long convergence time. Therefore, the state-of-the-art design method is not applicable to a CSAS design which requires real-time decision making. In this article, we address the problem by introducing MPC-CSAS, a Multi-Party Computation (MPC) based design approach for privacy-preserving CSAS. Our proposed method is simple to implement and applicable to all types of cost functions of vehicles. Moreover, our simulation results show that the proposed MPC-CSAS can achieve very promising system performance in just one algorithm iteration without using extra infrastructure for a typical CSAS. |
| 资助项目 | Science Foundation Ireland[SFI/12/RC/2289_P2] |
| WOS研究方向 | Engineering ; Transportation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:000732115400001 |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/17982]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Cheng, Long |
| 作者单位 | 1.Dublin City Univ, SFI Insight Ctr Data Analyt, Dublin D09 V209 9, Ireland 2.Wageningen Univ & Res, Informat Technol Grp, NL-6708 PB Wageningen, Netherlands 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 4.Dublin City Univ, Insight Ctr Data Analyt, Dublin D09 V209 9, Ireland 5.Dublin City Univ, Sch Comp, Dublin D09 V209 9, Ireland 6.Dublin City Univ, Sch Elect Engn, Dublin D09 V209 9, Ireland |
| 推荐引用方式 GB/T 7714 | Liu, Mingming,Cheng, Long,Gu, Yingqi,et al. MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2021:7. |
| APA | Liu, Mingming,Cheng, Long,Gu, Yingqi,Wang, Ying,Liu, Qingzhi,&O'Connor, Noel E..(2021).MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,7. |
| MLA | Liu, Mingming,et al."MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021):7. |
入库方式： OAI收割
来源：计算技术研究所
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