|
|
|
| Task allocation method for Internet of vehicles spatial crowdsourcing with privacy protection |
Xue-jiao LIU1( ),Hui-min WANG1,Ying-jie XIA2,*(),Si-wei ZHAO1 |
1. Key Laboratory of Cryptography of Zhejiang Province, School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
2. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China |
|
|
|
Abstract A task allocation method for Internet of vehicles spatial crowdsourcing with privacy protection was proposed under the blockchain architecture in order to solve the problem that centralized spatial crowdsourcing server in the traditional spatial crowdsourcing of Internet of vehicles was untrusted and vulnerable to malicious attacks, which posed a great threat to users’ privacy. A distributed and trusted spatial crowdsourcing system of Internet of vehicles was designed based on the blockchain technology. The multi-key homomorphic encryption algorithm was adopted to distribute tasks, which supported task allocation of location ciphertext data of different vehicle users (keys). Then the possibility of privacy disclosure of vehicle users was reduced. The experimental results show that the proposed method can effectively protect users’ privacy information, reduce the computing overhead of task allocation by 34.3% compared with the existing methods, and improve the efficiency of task allocation.
|
|
Received: 23 December 2021
Published: 26 July 2022
|
|
|
| Fund: 国家自然科学基金资助项目（61873232）；浙江省自然科学基金资助项目（LZ22F030004）；公安部重点实验室资助项目（2020DSJSYS005） |
|
Corresponding Authors:
Ying-jie XIA
E-mail: liuxuejiao@hznu.edu.cn;xiayingjie@zju.edu.cn
|
具有隐私保护的车联网空间众包任务分配方法
为了解决传统车联网空间众包中集中式空间众包服务器不可信和易遭受攻击给用户隐私带来极大威胁的问题，提出区块链架构下具有隐私保护的车联网空间众包任务分配方法. 基于区块链技术，设计分布式可信的车联网空间众包系统. 采用多密钥全同态加密算法实现任务分配，支持对不同车辆用户 (密钥) 的密文数据进行任务分配，降低隐私泄露的可能性. 实验分析表明，采用该方法能够有效地保护用户隐私信息，任务分配的计算时间开销与现有研究方法相比下降了34.3%，提高了任务分配的效率.
关键词：
车联网,
空间众包,
隐私保护,
任务分配,
区块链
|
|
| [1] |
KAZEMI L, SHAHABI C. Geocrowd: enabling query answering with spatial crowdsourcing [C]// Proceedings of the 20th International Conference on Advances in Geographic Information Systems. Redondo Beach: ACM, 2012: 189-198.
|
|
|
| [2] |
ZHANG C, ZHU L, XU C, et al A privacy-preserving traffic monitoring scheme via vehicular crowdsourcing[J]. Sensors, 2019, 19 (6): 1274
doi: 10.3390/s19061274
|
|
|
| [3] |
TONG Y, ZHOU Z, ZENG Y, et al Spatial crowdsourcing: a survey[J]. The VLDB Journal, 2020, 29 (1): 217- 250
doi: 10.1007/s00778-019-00568-7
|
|
|
| [4] |
HAN S, LIN J, ZHAO S, et al Location privacy-preserving distance computation for spatial crowdsourcing[J]. IEEE Internet of Things Journal, 2020, 7 (8): 7550- 7563
doi: 10.1109/JIOT.2020.2985454
|
|
|
| [5] |
LIU A, LI Z X, LIU G F, et al Privacy-preserving task assignment in spatial crowdsourcing[J]. Journal of Computer Science and Technology, 2017, 32 (5): 905- 918
doi: 10.1007/s11390-017-1772-5
|
|
|
| [6] |
LIN F, WEI J, LI J, et al Local privacy-preserving dynamic worker locations in spatial crowdsourcing[J]. IEEE Access, 2021, 9: 27359- 27373
doi: 10.1109/ACCESS.2021.3058574
|
|
|
| [7] |
HUANG C, LU R, ZHU H Privacy-friendly spatial crowdsourcing in vehicular networks[J]. Journal of Communications and Information Networks, 2017, 2 (2): 59- 74
doi: 10.1007/s41650-017-0017-7
|
|
|
| [8] |
NAKAMOTO S. Bitcoin: a peer-to-peer electronic cash system [EB/OL]. (2017-12-20). https:// bitcoin.org/bitcoin.pdf.
|
|
|
| [9] |
LIU X, DENG R H, CHOO K K R, et al An efficient privacy-preserving outsourced calculation toolkit with multiple keys[J]. IEEE Transactions on Information Forensics and Security, 2016, 11 (11): 2401- 2414
doi: 10.1109/TIFS.2016.2573770
|
|
|
| [10] |
LI M, WENG J, YANG A, et al CrowdBC: a blockchain-based decentralized framework for crowdsourcing[J]. IEEE Transactions on Parallel and Distributed Systems, 2018, 30 (6): 1251- 1266
|
|
|
| [11] |
YANG M, ZHU T, LIANG K, et al A blockchain-based location privacy-preserving crowdsensing system[J]. Future Generation Computer Systems, 2019, 94: 408- 418
doi: 10.1016/j.future.2018.11.046
|
|
|
| [12] |
ZHANG J, YANG F, MA Z, et al A decentralized location privacy-preserving spatial crowdsourcing for Internet of vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22 (4): 2299- 2313
|
|
|
| [13] |
WANG S, TAHA A F, WANG J. Blockchain-assisted crowdsourced energy systems[C]// 2018 IEEE Power and Energy Society General Meeting. Portland: IEEE, 2018: 1-5.
|
|
|
| [14] |
PINTO G, DIAS J P, FERREIRA H S. Blockchain-based PKI for crowdsourced IoT sensor information [C]// International Conference on Soft Computing and Pattern Recognition. Cham: Springer, 2018: 248-257.
|
|
|
| [15] |
WU Y, TANG S, ZHAO B, et al BPTM: Blockchain-based privacy-preserving task matching in crowdsourcing[J]. IEEE Access, 2019, 7: 45605- 45617
doi: 10.1109/ACCESS.2019.2908265
|
|
|
| [16] |
WANG L, LIU G, SUN L A secure and privacy-preserving navigation scheme using spatial crowdsourcing in fog-based vanets[J]. Sensors, 2017, 17 (4): 668
doi: 10.3390/s17040668
|
|
|
| [17] |
NIU B, LI Q, ZHU X, et al. Achieving k-anonymity in privacy-aware location-based services [C]//IEEE Conference on Computer Communications. Piscataway: IEEE, 2014: 754-762.
|
|
|
| [18] |
OU L, QIN Z, LIU Y, et al. Multi-user location correlation protection with differential privacy [C]// 2016 IEEE 22nd International Conference on Parallel and Distributed Systems. Wuhan: IEEE, 2016: 422-429.
|
|
|
| [19] |
TO H, GHINITA G, SHAHABI C A framework for protecting worker location privacy in spatial crowdsourcing[J]. Proceedings of the VLDB Endowment, 2014, 7 (10): 919- 930
doi: 10.14778/2732951.2732966
|
|
|
| [20] |
TO H, GHINITA G, FAN L, et al Differentially private location protection for worker datasets in spatial crowdsourcing[J]. IEEE Transactions on Mobile Computing, 2016, 16 (4): 934- 949
|
|
|
| [21] |
SHEN Y, HUANG L, LI L, et al. Towards preserving worker location privacy in spatial crowdsourcing [C]// 2015 IEEE Global Communications Conference. San Diego: IEEE, 2015: 1-6.
|
|
|
| [22] |
LIU A, WANG W, SHANG S, et al Efficient task assignment in spatial crowdsourcing with worker and task privacy protection[J]. GeoInformatica, 2018, 22 (2): 335- 362
doi: 10.1007/s10707-017-0305-2
|
|
|
| [23] |
LIU B, CHEN L, ZHU X, et al. Protecting location privacy in spatial crowdsourcing using encrypted data [C]// Proceedings of the 20th International Conference on Extending Database Technology. Venice:[s. n.], 2017: 478–481.
|
|
|
| [24] |
ZHANG J, JIANG Z L, LI P, et al Privacy-preserving multi-key computing framework for encrypted data in the cloud[J]. Information Sciences, 2021, 575: 217- 230
doi: 10.1016/j.ins.2021.06.017
|
|
|
| [25] |
ZHANG S, RAY S, LU R, et al Preserving location privacy for outsourced most-frequent item query in mobile crowdsensing[J]. IEEE Internet of Things Journal, 2021, 8 (11): 9139- 9150
doi: 10.1109/JIOT.2021.3056442
|
|
|
| [26] |
YANG D, XUE G, FANG X, et al. Crowdsourcing to smartphones: Incentive mechanism design for mobile phone sensing [C]// Proceedings of the 18th Annual International Conference on Mobile Computing and Networking. Istanbul: ACM, 2012: 173-184.
|
|
|
| [27] |
BRESSON E, CATALANO D, POINTCHEVAL D. A simple public-key cryptosystem with a double trapdoor decryption mechanism and its applications [C]// International Conference on the Theory and Application of Cryptology and Information Security. Berlin: Springer, 2003: 37-54.
|
|
|
| [28] |
HUANG X, ZHAO D, PENG H Empirical study of DSRC performance based on safety pilot model deployment data[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18 (10): 2619- 2628
doi: 10.1109/TITS.2017.2649538
|
|
|
| [29] |
YANG X, YI X, KHALIL I, et al A lightweight authentication scheme for vehicular ad hoc networks based on MSR[J]. Vehicular Communications, 2019, 15: 16- 27
doi: 10.1016/j.vehcom.2018.11.001
|
|
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
