一种云环境中密文数据的模糊多关键词检索方案

越来越多的企业和个人用户将大量的数据存储在云服务器。为了保障数据隐私,重要数据以密文形式存储在云端,但却给数据检索操作带来严峻挑战。传统的基于明文的检索方案不再适用,已有的基于密文的检索方案存在不支持模糊检索或多关键词检索、效率较低、空间开销较大、不支持检索结果排序等问题。因此,研究安全高效的密文检索方法具有重要意义。提出了一种新的云环境中密文数据的模糊多关键词检索方案,该方案能够从云服务器上检索出包含有指定多个关键词的密文,支持模糊关键词检索,并且不会向云服务器和其他攻击者泄露与数据和检索相关的任何明文信息；使用计数型布隆过滤器和MinHash算法构建索引向量和查询向量,使得索引构建和查询过程更加高效,且排序结果更加准确。安全性分析和性能评估表明该方案具有高安全性、可靠性、检索效率和准确率。

Fuzzy Multi-keyword Retrieval Scheme over Encrypted Data in Cloud Computing

Nowadays more and more enterprise and individual users store a large amount of data in the cloud.To protect data privacy,important data has to be encrypted before being stored in the cloud,which brings a severe challenge to the retrieval of data.Traditional retrieval schemes based on plaintext have not been applicable,and existing retrieval schemes based on ciphertext have many shortcomings,some of which do not support fuzzy search or multi-keyword search, poor efficiency or large space overhead,or do not return ranking results.Therefore,researching secure and efficient retrieval scheme on ciphertext is of great significance.A new fuzzy multi-keyword retrieval scheme over encrypted data in cloud computing was proposed,which can retrieve the ciphertext containing multiple keywords from cloud ser-ver,support fuzzy keyword search,and will not leak any plaintext information of data and retrieval to cloud server and other attackers.In the scheme,counting bloom filter and MinHash algorithm are used to construct index vectors and query vectors,which makes the process of building index and querying more efficient,and the ranking results more accurate.The security analysis and performance evaluation show that our scheme has high security,reliability,retrieval efficiency and accuracy.