矢量地理信息溯源记录组织验证的区块链技术

doi:10.11947/j.AGCS.2021.20200168

测绘学报 ›› 2021, Vol. 50 ›› Issue (6): 823-832.doi: 10.11947/j.AGCS.2021.20200168

矢量地理信息溯源记录组织验证的区块链技术

李皓¹, 乐鹏¹, 姜良存¹, 张明达², 梁哲恒³

1. 武汉大学遥感信息工程学院, 湖北武汉 430079;
2. 湖北大学资源环境学院, 湖北武汉 430062;
3. 广东南方数码科技股份有限公司, 广东广州 510665

收稿日期:2020-05-06 修回日期:2020-10-25 发布日期:2021-06-28
通讯作者: 乐鹏 E-mail:pyue@whu.edu.cn
作者简介:李皓(1996—),男,硕士生,研究方向为空间数据组织、区块链等。E-mail:leehomm@whu.edu.cn
基金资助:
国家自然科学基金（41722109；41901315；42071354）

Blockchain technology for vector geographic provenance information organization and verification

LI Hao¹, YUE Peng¹, JIANG Liangcun¹, ZHANG Mingda², LIANG Zheheng³

1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China;
3. Guangdong Nanfang Digital Technology Co., Ltd., Guangzhou 510665, China

Received:2020-05-06 Revised:2020-10-25 Published:2021-06-28
Supported by:
The National Natural Science Foundation of China(Nos. 41722109；41901315；42071354)

摘要/Abstract

摘要： 溯源问题是“新地理学”研究的一个重要议题，对于判断地理数据是否可靠、可用十分重要。在分布式协作环境下，地理溯源记录本身也面临着可靠性保证的问题。近年来快速发展的区块链技术因具有可信透明、不可篡改等特性，为溯源记录的可靠性管理提供了新的解决思路。然而，如何利用区块链对大量且具有不同粒度层级的地理溯源记录进行存储组织，成为一个难点。因此，本文以矢量数据为研究对象，探讨矢量溯源信息链上存储结构的设计要求，提出一种通过梅克尔帕特里夏树（Merkle Patricia tree，MPT）对不同层级的溯源信息进行链上组织的方法，并设计了相应的溯源验证算法。同时，本文开发了矢量溯源链原型系统，对链上的溯源信息进行了溯源验证试验。试验结果表明，相比通用的二叉梅克尔树，本文提出的链上存储组织方法与验证算法具有更高的验证性能。

关键词: 矢量数据溯源, 区块链, 溯源粒度, MPT结构, 溯源验证

Abstract: Provenance is an important research issue of “Neogeography”, and it plays a significant role in judging whether geospatial data is reliable or not. In a distributed collaborative environment, geospatial data provenance also faces reliability issues. Blockchain technology has gained rapid development in recent years due to its characteristics of credibility, transparency, and non-tampering. It provides a new solution to the reliability management of provenance records. However, how to use the blockchain to organize and store a large number of geospatial data provenance with different granularity levels remains a challenge. Therefore, taking vector data as the research object, this paper discusses the requirements in designing the structure of provenance blockchain, and proposes a method of organizing on-chain provenance information at different levels based on Merkle Patricia tree (MPT). Further, an algorithm that is suitable for the verification of vector provenance information is provided.This paper develops a vector data provenance blockchain prototype system, and conducts verification experiments using the vector provenance information. The experiments demonstrate that MPT can achieve higher performance than binary Meckel tree in vector data provenance verification.

Key words: vector data provenance, blockchain, provenance granularity, MPT structure, provenance verification

中图分类号:

P208

李皓, 乐鹏, 姜良存, 张明达, 梁哲恒. 矢量地理信息溯源记录组织验证的区块链技术[J]. 测绘学报, 2021, 50(6): 823-832.

LI Hao, YUE Peng, JIANG Liangcun, ZHANG Mingda, LIANG Zheheng. Blockchain technology for vector geographic provenance information organization and verification[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50(6): 823-832.

参考文献

[1] 乐鹏, 郭霞, 张晨晓, 等. 空间数据溯源的概念、模型与服务[J]. 地理与地理信息科学, 2015, 31(6): 1-7, 14. YUE Peng, GUO Xia, ZHANG Chenxiao, et al. Geospatial data provenance: concept, model and services[J]. Geography and Geo-Information Science, 2015, 31(6): 1-7, 14.
[2] 单杰, 秦昆, 黄长青, 等. 众源地理数据处理与分析方法探讨[J]. 武汉大学学报(信息科学版), 2014, 39(4): 390-396. SHAN Jie, QIN Kun, HUANG Changqing, et al. Methods of crowd sourcing geographic data processing and analysis[J]. Geomatics and Information Science of Wuhan University, 2014, 39(4): 390-396.
[3] 赵肄江, 周晓光. 地理信息志愿者信誉度评估的版本相似度模型——以面目标为例[J]. 测绘学报, 2015, 44(5): 578-584. DOI: 10.11947/j.AGCS.2015.20140065. ZHAO Yijiang, ZHOU Xiaoguang. Version similarity-based model for volunteers’ reputation of volunteered geographic information: a case study of polygon[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(5): 578-584. DOI: 10.11947/j.AGCS.2015.20140065.
[4] JIANG Liangcun, YUE Peng, KUHN W, et al. Advancing interoperability of geospatial data provenance on the web: gap analysis and strategies[J]. Computers & Geosciences, 2018, 117: 21-31.
[5] 乐鹏, 彭飞飞, 龚健雅. 基于SOA的空间数据起源研究[J]. 地理与地理信息科学, 2010, 26(3): 6-10. YUE Peng, PENG Feifei, GONG Jianya. Research on SOA-based geospatial data provenance[J]. Geography and Geo-Information Science, 2010, 26(3): 6-10.
[6] 姜良存. 空间数据溯源建模与语义计算方法研究[J]. 地理与地理信息科学, 2019, 35(3): 142. JIANG Liangcun. Study of geospatial data provenance modelling and semantic computation[J]. Geography and Geo-Information Science, 2019, 35(3): 142.
[7] YUAN Jie, YUE Peng, GONG Jianya, et al. A linked data approach for geospatial data provenance[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(11): 5105-5112.
[8] DI Liping, YUE Peng, RAMAPRIYAN H K, et al. Geoscience data provenance: an overview[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(11): 5065-5072.
[9] DI Liping, SHAO Yuanzheng, KANG Lingjun. Implementation of geospatial data provenance in a web service workflow environment with ISO 19115 and ISO 19115-2 lineage model[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(11): 5082-5089.
[10] CLOSA G, MASÓ J, PROß B, et al. W3C PROV to describe provenance at the dataset, feature and attribute levels in a distributed environment[J]. Computers, Environment and Urban Systems, 2017, 64: 103-117.
[11] CLOSA G, MASÓ J, ZABALA A, et al. A provenance metadata model integrating ISO geospatial lineage and the OGC WPS: conceptual model and implementation[J]. Transactions in GIS, 2019, 23(5): 1102-1124.
[12] ZHANG Mingda, JIANG Liangcun, ZHAO Jing, et al. Coupling OGC WPS and W3C PROV for provenance-aware geoprocessing workflows[J]. Computers & Geosciences, 2020, 138: 104419.
[13] 赵珂, 王楠. 中间-人·大平台——角色定位下的城市规划大数据“资产化”[J]. 西部人居环境学刊, 2014, 29(6): 95-100. ZHAO Ke, WANG Nan. Middleman and big platform: the big data “capitalization” of urban planning based on the role orientation[J]. Journal of Human Settlements in West China, 2014, 29(6): 95-100.
[14] 龚健雅, 张翔, 向隆刚, 等. 智慧城市综合感知与智能决策的进展及应用[J]. 测绘学报, 2019, 48(12): 1482-1497. DOI: 10.11947/j.AGCS.2019.20190464. GONG Jianya, ZHANG Xiang, XIANG Longgang, et al. Progress and applications for integrated sensing and intelligent decision in smart city[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12): 1482-1497. DOI: 10.11947/j.AGCS.2019.20190464.
[15] BOULOS M N K, WILSON J T, CLAUSON K A. Geo-spatial blockchain: promises, challenges, and scenarios in health and healthcare[J]. International Journal of Health Geographics, 2018, 17(1): 25.
[16] 袁勇, 王飞跃. 区块链技术发展现状与展望[J]. 自动化学报, 2016, 42(4): 481-494. YUAN Yong, WANG Feiyue. Blockchain: the state of the art and future trends[J]. Acta Automatica Sinica, 2016, 42(4): 481-494.
[17] RAMACHANDRAN A, KANTARCIOGLU D. Smartprovenance: a distributed, blockchain based data provenance system[C]//Proceedings of the 8th ACM Conference on Data and Application Security and Privacy. Tempe, AZ: ACM, 2018: 35-42.
[18] NEISSE R, STERI G, NAI-FOVINO I. A blockchain-based approach for data accountability and provenance tracking[C]//Proceedings of the 12th International Conference on Availability, Reliability and Security. Reggio Calabria: ACM, 2017: 1-10.
[19] DEMICHEV A, KRYUKOV A, PRIKHODKO N. The approach to managing provenance metadata and data access rights in distributed storage using the hyperledger blockchain platform[C]//Proceedings of 2018 Ivannikov Ispras Open Conference (ISPRAS). Moscow: IEEE, 2018: 131-136.
[20] LIANG Xueping, SHETTY S, TOSH D, et al. ProvChain: a blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability[C]//Proceedings of the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). Madrid: IEEE, 2017: 468-477.
[21] RUAN Pingcheng, CHEN Gang, DINH T T A, et al. Fine-grained, secure and efficient data provenance on blockchain systems[J]. Proceedings of the VLDB Endowment, 2019, 12(9): 975-988.
[22] YUE Peng, ZHANG Mingda, GUO Xia, et al. Granularity of geospatial data provenance[C]//Proceedings of 2014 IEEE Geoscience and Remote Sensing Symposium. Quebec City, QC: IEEE, 2014: 4492-4495.
[23] HE Lianlian, YUE Peng, DI Liping, et al. Adding geospatial data provenance into SDI: a service-oriented approach[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(2): 926-936.
[24] MISSIER P, BELHAJJAME K, CHENEY J. The W3C PROV family of specifications for modelling provenance metadata[C]//Proceedings of the 16th International Conference on Extending Database Technology. Genoa: ACM, 2013: 773-776.
[25] CORON J S, DODIS Y, MALINAUD C, et al. Merkle-Damgård revisited: how to construct a hash function[C]//Proceedings of the 25th Annual International Conference on Advances in Cryptology. Berlin: Springer-Verlag, 2005: 430-448.
[26] GRINBERG R. Bitcoin: an innovative alternative digital currency[J]. Hastings Science and Technology Law Journal, 2012, 4(2): 160.
[27] 邵奇峰, 金澈清, 张召, 等. 区块链技术: 架构及进展[J]. 计算机学报, 2018, 41(5): 969-988. SHAO Qifeng, JIN Cheqing, ZHANG Zhao, et al. Blockchain: architecture and research progress[J]. Chinese Journal of Computers, 2018, 41(5): 969-988.

矢量地理信息溯源记录组织验证的区块链技术

Blockchain technology for vector geographic provenance information organization and verification

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics

本文评价