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作 者:信俊昌 崔婷钰 郝琨 徐浚铭 王之琼[3] 黄敏[4] XIN Junchang;CUI Tingyu;HAO Kun;XU Junming;WANG Zhiqiong;HUANG Min(School of Computer Science and Engineering,Northeastern University,Shenyang 110819,China;Key Laboratory of Big Data Management and Analytics(Liaoning Province),Shenyang 110819,China;School of Medicine and Biological Information Engineering,Northeastern University,Shenyang 110179,China;School of Information Science and Engineering,Northeastern University,Shenyang 110819,China)
机构地区:[1]东北大学计算机科学与工程学院,沈阳110819 [2]辽宁省大数据管理与分析重点实验室,沈阳110819 [3]东北大学医学与生物信息工程学院,沈阳110179 [4]东北大学信息科学与工程学院,沈阳110819
出 处:《计算机工程与应用》2025年第4期282-288,共7页Computer Engineering and Applications
基 金:国家重点研发计划(2021YFB3300900);国家自然科学基金(62072089)。
摘 要:随着分片联盟链技术的发展,大量具有内在联系的数据被分散存储在不同分片,溯源查询操作变得复杂。现有研究仅支持单一分片的溯源查询操作,直接进行跨分片溯源将产生查询延迟高和结果验证弱的问题,影响用户体验和结果可信性。针对以上问题,提出了一种分片联盟链中的可验证溯源查询框架CPP。为了便于跨分片溯源操作,提升查询效率,以属性为单位,设计了新颖的三层索引结构SBP(sharding-block-proofindex)。为了防止因索引被篡改造成的结果不可信,设计了索引防篡改机制。为了防止因恶意节点篡改或删除部分结果造成的结果不可信,设计了支持任意维度属性动态聚合的可验证溯源查询算法,使得用户能够对返回结果的完整性和正确性进行验证。在真实公开数据集上进行实验,验证了所提出方法的高效性和有效性。With the development of sharding consortium blockchain technology,a large amount of intrinsically related data is scattered and stored in different shards,and the provenance query operation becomes complex.The existing research only supports the provenance query operation of a single shard,and direct cross-shard provenance will cause problems of high query latency and weak result verification,which will affect the user experience and the credibility of the results.In order to solve the above problems,a verifiable provenance query framework CPP in sharding consortium chain is pro-posed.In order to facilitate cross-shard provenance operations and improve query efficiency,a novel three-layer index structure SBP(sharding-block-proof index)is designed based on attributes.In order to prevent the results of index tampering from being untrustworthy,an index tamper-proof mechanism is designed.In order to prevent the untrustworthy results caused by malicious nodes tampering with or deleting some of the results,a verifiable provenance query algorithm that supports the dynamic aggregation of arbitrary dimensional attributes is designed,so that users can verify the completeness and correctness of the returned results.Finally,experiments are carried out on real public datasets to verify the efficiency and effectiveness of the proposed method.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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