Research Of Encrypted Data Searching Technology In Cloud Based On Secure Knn

Cloud computing has been considered as a new model of enterprise IT infrastructure, which can organize huge resource of computing, storage and applications, and enable users to enjoy ubiquitous, convenient and on-demand network access to a shared pool of configurable computing resources with great efficiency and minimal economic overhead. Attracted by these appealing features, both individuals and enterprises are motivated to outsource their data to the cloud, instead of purchasing software and hardware to manage the data themselves.Despite of the various advantages of cloud services, outsourcing sensitive information to remote servers brings privacy concerns. In practice, a general approach to protect the data confidentiality is to encrypt the data before outsourcing to the commercial public cloud. This, however, obsoletes the traditional data utilization like data search. Clearly, it is impractical to download all the data from cloud and decrypt locally, and having data stored on the cloud serves makes no purpose unless they can be easily searched and utilized. Thus, exploring privacy-preserving and effective search service over encrypted cloud data is of paramount importance.At present, most of the existing techniques about encrypted data searching mainly focus on encrypted documents searching, only few works are designed for searching over encrypted images. In terms of encrypted documents searching, there is no work simultaneously supporting multi-keyword ranked search and dynamic update operations. Besides, none of the existing works take the problem of unauthorized copy distribution after search into consideration. To solve these two problems, we design two schemes based on secure kNN algorithm in this paper. The specific research works are summarized as follows:1) A secure multi-keyword ranked search scheme over encrypted documents supporting dynamic updateFirstly, this paper presents a secure multi-keyword ranked search scheme over encrypted documents, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used term frequency-inverse document frequency model are combined in the index construction and query generation. We construct a special tree-based index structure and propose a "Greedy Depth-first Search" algorithm to provide efficient multi-keyword ranked search. Due to the special structure of our tree-based index, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. Besides, to deal with different attacks in two different threat models, two secure search schemes are proposed based on the secure kNN algorithm. Extensive experiments and the security analysis demonstrate the efficiency and security of the proposed schemes.2) A secure similarity search scheme over encrypted images supporting copy deterrenceSecondly, this paper proposes a secure similarity search scheme over encrypted images that supports copy deterrence. Specifically, an index based on pre-filter table is constructed to provide efficient search. And four types of image features are chosen to test the search precision. To protect search privacy, a secure search scheme based on secure kNN algorithm is proposed under the threat model. Moreover, to address the problem of copy deterrence, an encryption domain watermark protocol is integrated into the search scheme, which efficiently tracks dishonest user who distributes the images to unauthorized persons. The security analysis and extensive experiments show the security and efficiency of our proposed schemes.