云计算环境下保护隐私的关键字查询关键技术研究

发布时间：2018-06-09 03:15

本文选题：云计算 + 隐私保护　；参考：《北京邮电大学》2016年博士论文

【摘要】：随着数据服务的规模以及用户量的快速增长,数据拥有者在本地提供数据服务的成本日趋提高。越来越多的数据拥有者希望将其数据服务外包到云计算平台中,从而有效地降低本地资源的开销,节约数据服务的运营成本。然而,直接将数据服务外包到云计算平台中会引起严重的隐私问题。数据服务中的隐私信息可能被恶意的攻击者或者云计算平台提供商获取,并从中获取商业利益,侵犯了数据拥有者和数据用户的隐私。随着互联网技术的快速发展,基于关键字查询的数据服务在现实生活中得到了广泛的应用。因此,如何在云计算环境下提供保护隐私的关键字查询服务是当前研究的热点问题。为了在云计算环境下提供用户体验更好的、多样化的关键字查询服务,本文针对三种重要的关键字查询技术在云计算环境下面临的隐私安全问题展开了深入的研究,主要解决了云计算环境下保护隐私的相似关键字排名查询问题、云计算环境下保护隐私的空间关键字查询问题以及云计算环境下保护隐私的图上关键字查询问题。主要贡献如下:(1)针对云计算环境下保护隐私的相似关键字排名查询问题,提出了保护隐私的相似关键字top-k查询方法。基于关键字的编辑距离及其在文档中的相关度构造了相似关键字集合,以支持相似关键字排名查询技术。通过对相似关键字集合及其相关度信息的加密,构建了一种新的、安全高效的树形查询索引,并在该索引的基础上提出了保护隐私的相似关键字top-k查询算法,在保证查询过程中隐私信息安全的前提下,支持在文本数据上的相似关键字排名查询。理论分析证明了该方法具备查询有效性和隐私安全性,实验结果说明了该方法具有较好的查询性能。(2)针对云计算环境下保护隐私的空间关键字查询问题,提出了保护隐私的空间关键字top-k查询方法。首先,基于空间文本数据的一致性加密算法构建了一种安全的空间文本数据查询索引。为了在安全索引的基础上实现高效精准的空间关键字查询,进一步提出了锚点辅助的位置关系判断算法和位置区分的查询陷门生成算法,来支持密文下精确的空间文本相似度计算。同时,为了满足大规模空间文本数据处理的性能要求,提出了一种基于关键字的安全剪枝算法来提高查询过程中的查询效率。理论分析证明了该方法具有查询有效性和安全性,实验结果说明了该方法具有较好的查询性能和可扩展性。(3)针对云计算环境下保护隐私的图上关键字查询问题,提出了保护隐私的图上最近关键字查询方法。通过对图数据的最短路径生成树及其节点上的关键字信息的加密,构造了一个安全的两级索引结构。同时,为了保护查询请求中的隐私信息,基于保护隐私的集合交集计算技术,提出了一种针对查询关键字的查询陷门生成算法。利用安全的两级索引和用户的查询陷门,提出了保护隐私的图上最近关键字查询算法,该算法能够在保护查询中隐私信息安全性的前提下,高效地实现图数据中的最近关键字查询。理论分析证明了该方法具备查询有效性和安全性,同时,实验结果说明了该方法具有较高的查询效率。
[Abstract]:With the scale of data services and the rapid growth of users, the cost of data owners in providing data services locally is increasing. More and more data owners want to outsource their data services to the cloud computing platform to effectively reduce the cost of local resources and save the operating costs of data services. The outsourcing of data services to the cloud computing platform can cause serious privacy issues. Privacy information in data services may be obtained by a malicious attacker or cloud computing platform provider, obtaining business benefits from it and violating the privacy of data owners and data users. With the rapid development of interconnected technologies, keyword queries are based on the rapid development of interconnected technology. Data services have been widely used in real life. Therefore, how to provide keyword search services to protect privacy in the cloud computing environment is a hot issue in the current research. In order to provide a better user experience in the cloud computing environment and diversified keyword query service, this paper aims at three important key query techniques. The problem of privacy security in cloud computing environment is deeply researched, which mainly solves the query problem of similar keyword ranking for privacy protection under the cloud computing environment, the problem of spatial keyword search for privacy protection under the cloud computing environment and the key key query on protecting hidden privacy under cloud computing environment. The following are as follows: (1) a similar keyword Top-k query method for protecting privacy is proposed to protect privacy in the cloud computing environment. A similar keyword set is constructed based on the edit distance of the keyword and its correlation in the document to support similar keyword ranking query technology. A new, secure and efficient tree type query index is constructed by encryption of set and its correlation information. On the basis of this index, a similar keyword Top-k query algorithm for privacy protection is proposed. On the premise of ensuring the security of privacy information in the query process, a similar keyword ranking query on the text data is supported. The results show that the method has query effectiveness and privacy security. The experimental results show that the method has good query performance. (2) a spatial keyword Top-k query method for privacy protection is proposed for privacy preserving spatial keyword query in cloud computing environment. First, the consistency encryption algorithm based on spatial text data is used. A secure spatial text data query index is constructed. In order to implement efficient and accurate spatial keyword query on the basis of secure index, the location relationship judgment algorithm of anchored point assisted and the location differentiation algorithm for query trapdoor generation are proposed to support the accurate spatial text similarity calculation under the ciphertext. In order to meet the performance requirements of large-scale spatial text data processing, a secure pruning algorithm based on keywords is proposed to improve query efficiency in the query process. The theoretical analysis shows that the method has query effectiveness and security. The experimental results show that the method has good query performance and scalability. (3) for the cloud meter, the method has a good query performance and scalability. A new keyword query method for protecting privacy is proposed. A secure two level index structure is constructed through the encryption of the shortest path spanning tree and the keyword information on the node. At the same time, in order to protect the privacy information in the query request, it is based on the key query method. In order to protect privacy of collection intersection computing technology, an algorithm for query trapdoor generation for query keyword is proposed. Using secure two level index and user's query trap door, the nearest keyword search algorithm for protecting privacy is proposed. This algorithm can efficiently implement the graph under the premise of protecting the security of privacy information in the query. The theoretical analysis shows the validity and security of the method. At the same time, the experimental results show that the method has high query efficiency.
【学位授予单位】：北京邮电大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TP393.09;TP309

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