基于布隆过滤器查找树的日志数据区块链溯源机制  

Blockchain-Based Log Data Provenance Mechanism Using Bloom Filter Search Tree

作　　者：张鹏 罗文华[1] ZHANG Peng;LUO Wenhua(School of Public Security Information Technology and Intelligence,Criminal Investigation Police University of China,Shenyang 110035,China)

机构地区：[1]中国刑事警察学院公安信息技术与情报学院,沈阳110035

出　　处：《信息网络安全》2024年第11期1739-1748,共10页Netinfo Security

基　　金：国家重点研发计划(2021YFC3301801)。

摘　　要：,文章提出一种以访问时间为核心索引信息的BT-BFT机制,将时间戳通过位图进行索引,利用布隆过滤器实现日志数据分析粒度的刻画,并构造均衡分布的树状结构,从而高效映射和索引时间维度的数据。该机制通过智能合约的形式进行部署,有效排查非目标溯源节点,支持时间戳溯源和基于关键词的全时段溯源,并引入身份过滤机制,以应对布隆过滤器固有的冲突问题。实验结果表明,文章所提机制能够在保证数据安全的前提下,高效且准确地对时间敏感类数据进行溯源。To address the shortcomings of existing provenance mechanisms in handling log data,this article proposed a blockchain-based log data provenance mechanism using Bloom filter search tree.This mechanism adopted a storage model combining on-chain data hashes and off-chain actual data was adopted to ensure data security and privacy.For the on-chain data hashes,this article introduced a bittimemap-Bloom filter tree(BT-BFT)mechanism centered around access time as the core index information.This mechanism indexed timestamps using a bitmap,then leveraged the number of Bloom filters to delineate the granularity of log data analysis,subsequently constructing a balanced tree-like structure that enabled efficient mapping and indexing of time-dimensional data.Deployed in the form of smart contracts,it effectively filtered out non-target provenance nodes,supported timestamp-based provenance and full-period provenance based on keywords,and incorporated an identity filtering mechanism to address the inherent conflict issues of Bloom filters.Experimental results demonstrate that the mechanism proposed in the article can accurately and efficiently trace time-sensitive data while ensuring data security.

关 键 词：区块链 日志数据 数据溯源 布隆过滤器 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]