20-03-2017, 04:51 PM
Cloud computing economically allows the paradigm of outsourcing data services. However, to protect the privacy of data, sensitive cloud data must be encrypted before it is outsourced to the commercial public cloud, which makes the data usage service a very difficult task. Although traditional search encryption techniques allow users to confidently search for encrypted data through keywords, they only support Boolean search and are not sufficient to satisfy the actual data usage need that is inherently demanded by a large number of Users and lots of data files in the cloud. In this article, we define and solve the problem of safe keyword search over encrypted data in the cloud. The classified search greatly improves the usability of the system by allowing the ranking of relevance of search results instead of sending undifferentiated results and, in addition, ensures the accuracy of file retrieval. Specifically, we explore the approach of statistical measurement, ie, relevance score, from retrieving information to constructing a secure search index, and developing a one-to-many order preservation mapping technique to adequately protect such information Sensitive score. The resulting design is able to facilitate efficient classification on the server side without losing the privacy of the keywords. A thorough analysis shows that our proposed solution enjoys a security guarantee "as strong as possible" compared to previous encryption schemes, while also correctly accomplishing the goal of classified keyword search. Extensive experimental results demonstrate the effectiveness of the proposed solution.
