A Survey on Blockchain-Based Trusted Data Elements Circulation

doi:10.11871/jfdc.issn.2096-742X.2023.05.005

Abstract

Abstract:

[Background] Data has become a kind of fundamental strategic resource for economic development. To fully leverage the value of data elements, a trusted data circulation system needs to be established. [Objective] As a new type of trusted data management platform, blockchain can realize the basic needs of trusted data circulation. Therefore, we discuss the trusted circulation technology of data elements based on blockchain in this survey. [Methods] From the perspective of establishing a trusted data circulation system, we first analyze the basic requirements of building a trusted circulation system for data elements. Then, we analyze the main techniques for realizing trusted circulation of data based on blockchain. Finally, we summarize current research works in the research field of blockchain that can be utilized to achieve the mentioned goals and present prospects for future research directions. [Results] Focusing on the aspects of enhancing data availability, credibility, negotiability, and traceability, we summarize and analyze the storage model, system performance scaling methods, data verification techniques, cross-chain techniques, and data provenance techniques of the existing blockchain system. [Conclusions] The existing methods can realize the trusted circulation system of data elements to some extent, yet there are still several unresolved problems in data privacy, utilization, and description.

Key words: blockchains, circulation of data elements, data management, data storage, sharding, cross-chain, provenance

ZHONG Ziyue, ZHU Changhao, LI Junzhe, ZHANG Meihui. A Survey on Blockchain-Based Trusted Data Elements Circulation[J]. Frontiers of Data and Computing, 2023, 5(5): 46-62, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2023.05.005.

Figures/Tables 2

Table 1

Table 2

Comparison of ADS-based trusted data query techniques"

ADS类型	ADS	支持的查询种类	证明大小	证明生成时间	证明验证时间	特点
基于哈希	Merkle Tree^[37]	布尔查询	$O (l o g n)$	$O (l o g n)$	$O (l o g n)$	构造简单，适用范围广
	MPT^[7]	键值查询	—	—	—	提高访问效率
	MBT^[38]	键值查询	$O (l o g b)$	$O (l o g b)$	$O (l o g b)$	避免数据聚集
	Merkle B-tree^[22]	范围查询	$O (l o g n)$	$O (l o g n)$	$O (l o g n)$	对更新顺序敏感
基于密码学累加器	vChain^[41]	布尔查询范围查询	$O (1)$	$O (n)$	$O (1)$	查询依赖数据编码
基于密码学累加器	vChain+^[42]	多维查询范围查询组合查询	$O (1)$	$O (n)$	$O (1)$	查询能力强，提升查询效率

Table 2

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系统名称	许可类型	存储模型	扩展方案	跨分片事务	TPS
SEBDB^[12-13]	许可链	关系型	链下扩展	-	10²~10³
BRD^[14]	许可链	关系型	-	-	10²~10³
FalconDB^[15]	许可链	关系型	-	-	10²~10⁴
Elastico^[25]	无许可链	键-值型	分片	不支持	N/A
OmniLedger^[26]	无许可链	键-值型	分片	支持	10⁴~10⁶
Monoxide^[27]	无许可链	键-值型	分片	支持	10⁴
BrokerChain^[28]	无许可链	键-值型	分片	支持	10³
SharPer^[32]	许可链	键-值型	分片	支持	10⁴
Pyramid^[33]	许可链	键-值型	分片	支持	10³~10⁴
Meepo^[34]	许可链	键-值型	分片	支持	10⁴~10⁵
GriDB^[35]	许可链	关系型	分片	支持	10³