Decentralized and Privacy-Preserving Smart Parking with Secure Repetition and Full Verifiability

被引：0
|
作者：
Li, Meng [1 ,2 ,3 ,4 ]
Zhang, Mingwei [1 ,2 ,3 ,4 ]
Zhu, Liehuang [5 ]
Zhang, Zijian [5 ,6 ]
Conti, Mauro [7 ,8 ]
Alazab, Mamoun [9 ]
机构：
[1] Key Laboratory of Knowledge Engineering with Big Data, Hefei University of Technology, Ministry of Education, Hefei,230002, China
[2] School of Computer Science and Information Engineering, Hefei University of Technology, Hefei,230002, China
[3] Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei,230002, China
[4] Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei University of Technology, Hefei,230002, China
[5] School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing,100081, China
[6] Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beijing,100081, China
[7] Department of Mathematics and HIT Center, University of Padua, Padua,35131, Italy
[8] Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft,2628, Netherlands
[9] College of Engineering, IT and Environment, Charles Darwin University, Casuarina,NT,0810, Australia
来源：
IEEE Transactions on Mobile Computing | 2024年 / 23卷 / 12期
关键词：
Smart Parking Services (SPSs) enable cruising drivers to find the nearest parking lot with available spots; reducing the traveling time; gas; and traffic congestion. However; drivers risk the exposure of sensitive location data during parking query to an untrusted Smart Parking Service Provider (SPSP). Our motivation arises from a repetitive query to an updated database; i.e; how a driver can be repetitively paired with a previously-matched-but-forgotten lot. Meanwhile; we aim to achieve repetitive query in an oblivious and unlinkable manner. In this work; we present Mnemosyne 2: decentralized and privacy-preserving smart parking with secure repetition and full verifiability. Specifically; we design repetitive; oblivious; and unlinkable Secure k Nearest Neighbor (Sk NN) with basic verifiability (correctness and completeness) for encrypted-and-updated databases. We build a local Ethereum blockchain to perform driver-lot matching via smart contracts. To adapt to the lot count update; we resort to the immutable blockchain for advanced verifiability (truthfulness). Last; we utilize decentralized blacklistable anonymous credentials to guarantee identity privacy. Finally; we formally define and prove privacy and security. We conduct extensive experiments over a real-world dataset and compare Mnemosyne2 with existing work. The results show that a query only needs 8 seconds (175 ms) on average for service waiting (verification) among 500 drivers. © 2002-2012 IEEE;
D O I：
10.1109/TMC.2024.3397687
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摘要：
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页码：11635 / 11654
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