对加密XML文档进行高效的树模式查询

Fang-Yu Rao, Jianneng Cao, Mehmet Kuzu, E. Bertino, Murat Kantarcioglu
{"title":"对加密XML文档进行高效的树模式查询","authors":"Fang-Yu Rao, Jianneng Cao, Mehmet Kuzu, E. Bertino, Murat Kantarcioglu","doi":"10.1145/2457317.2457338","DOIUrl":null,"url":null,"abstract":"Outsourcing XML documents is a challenging task, because it encrypts the documents, while still requiring efficient query processing. Past approaches on this topic either leak structural information or fail to support searching that has constraints on XML node content. In addition, they adopt a filtering-and-refining framework, which requires the users to prune false positives from the query results. To address these problems, we present a solution for efficient evaluation of tree pattern queries (TPQs) on encrypted XML documents. We create a domain hierarchy, such that each XML document can be embedded in it. By assigning each node in the hierarchy a position, we create for each document a vector, which encodes both the structural and textual information about the document. Similarly, a vector is created also for a TPQ. Then, the matching between a TPQ and a document is reduced to calculating the distance between their vectors. For the sake of privacy, such vectors are encrypted before being outsourced. To improve the matching efficiency, we use a k-d tree to partition the vectors into non-overlapping subsets, such that non-matchable documents are pruned as early as possible. The extensive evaluation shows that our solution is efficient and scalable to large dataset.","PeriodicalId":374808,"journal":{"name":"Trans. Data Priv.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Efficient tree pattern queries on encrypted XML documents\",\"authors\":\"Fang-Yu Rao, Jianneng Cao, Mehmet Kuzu, E. Bertino, Murat Kantarcioglu\",\"doi\":\"10.1145/2457317.2457338\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Outsourcing XML documents is a challenging task, because it encrypts the documents, while still requiring efficient query processing. Past approaches on this topic either leak structural information or fail to support searching that has constraints on XML node content. In addition, they adopt a filtering-and-refining framework, which requires the users to prune false positives from the query results. To address these problems, we present a solution for efficient evaluation of tree pattern queries (TPQs) on encrypted XML documents. We create a domain hierarchy, such that each XML document can be embedded in it. By assigning each node in the hierarchy a position, we create for each document a vector, which encodes both the structural and textual information about the document. Similarly, a vector is created also for a TPQ. Then, the matching between a TPQ and a document is reduced to calculating the distance between their vectors. For the sake of privacy, such vectors are encrypted before being outsourced. To improve the matching efficiency, we use a k-d tree to partition the vectors into non-overlapping subsets, such that non-matchable documents are pruned as early as possible. The extensive evaluation shows that our solution is efficient and scalable to large dataset.\",\"PeriodicalId\":374808,\"journal\":{\"name\":\"Trans. Data Priv.\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trans. Data Priv.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2457317.2457338\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trans. Data Priv.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2457317.2457338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

摘要

外包XML文档是一项具有挑战性的任务,因为它加密了文档,同时仍然需要有效的查询处理。过去关于此主题的方法要么泄漏结构信息,要么不支持对XML节点内容有约束的搜索。此外,它们采用了过滤和精炼框架,该框架要求用户从查询结果中剔除误报。为了解决这些问题,我们提出了一种对加密XML文档进行树模式查询(tpq)有效评估的解决方案。我们创建了一个域层次结构,这样每个XML文档都可以嵌入其中。通过为层次结构中的每个节点分配一个位置,我们为每个文档创建了一个向量,该向量对文档的结构信息和文本信息进行编码。类似地,也为TPQ创建一个向量。然后,将TPQ与文档之间的匹配简化为计算其向量之间的距离。为了保护隐私,这些载体在外包之前都是加密的。为了提高匹配效率,我们使用k-d树将向量划分为不重叠的子集,以便尽早修剪不匹配的文档。广泛的评估表明,我们的解决方案是有效的和可扩展的大数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient tree pattern queries on encrypted XML documents
Outsourcing XML documents is a challenging task, because it encrypts the documents, while still requiring efficient query processing. Past approaches on this topic either leak structural information or fail to support searching that has constraints on XML node content. In addition, they adopt a filtering-and-refining framework, which requires the users to prune false positives from the query results. To address these problems, we present a solution for efficient evaluation of tree pattern queries (TPQs) on encrypted XML documents. We create a domain hierarchy, such that each XML document can be embedded in it. By assigning each node in the hierarchy a position, we create for each document a vector, which encodes both the structural and textual information about the document. Similarly, a vector is created also for a TPQ. Then, the matching between a TPQ and a document is reduced to calculating the distance between their vectors. For the sake of privacy, such vectors are encrypted before being outsourced. To improve the matching efficiency, we use a k-d tree to partition the vectors into non-overlapping subsets, such that non-matchable documents are pruned as early as possible. The extensive evaluation shows that our solution is efficient and scalable to large dataset.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信