Towards Practical Schemes For Searching The Encrypted Cloud Data

Due to the great advances in cloud computing and Internet technologies, data owners have been motivated to outsource the storage of their data to remote cloud servers to enjoy great data management service with an efficient cost. However, cloud computing has introduced new security risks that need to be addressed well to accelerate the wide adoption for this new technology. For security purposes, data owners usually have to encrypt their data prior to outsourcing it to the untrusted cloud servers. But traditional encryption schemes are inadequate since they make indexing and searching the encrypted data more challenging tasks. Recently, several schemes have been provided to enable searching over the encrypted data. Such schemes are called searchable encryption (SE) schemes. However, these schemes have several limitations that need to be solved to make the application of such schemes more practical to the users of the cloud computing. First, the majority of the current SE schemes are limited to handling an exact search, not a similarity search; but the latter is an important need for all the current information retrieval systems. Second, the current similarity SE schemes are impractical for real world applications because these systems require touching the entire index during the search process, as well as incurring substantial storage cost. Third, the majority of SE schemes are limited to handling either a single keyword search or a Boolean search but not a multi-keyword ranked search, a more efficient model to retrieve the top documents corresponding to the provided keywords. Fourth, these systems are designed to search a single data source.In this dissertation, four methods to mitigate the above listed limitations have been presented. The first method allows the cloud server to answer even the mistyped queries, while preserving the privacy of the query trapdoor. The work presented in this dissertation focuses on constructing a flexible secure index that allows the cloud server to perform the approximate search operations without revealing the content of the query trapdoor or the index content.The second method proposes an efficient yet secure scheme to search the encrypted cloud data, while recovering the misspellings and typographical errors that exist frequently both in the search request and in the source data. The metric spaces and embedding methods have been used to construct a tree-based index, which allows retrieving only the relevant entries with a minimum number of distance evaluations.The third method proposes a secure multi-keyword ranked search scheme over the encrypted cloud data. Such scheme allows an authorized user to retrieve the most relevant documents in a descending order, while preserving the privacy of his search request and the contents of documents he retrieved.The fourth method allows the authorized user to search the distributed servers with multi-keyword queries and retrieve the most relevant documents in a descending order with respect to their relevance to the query, while preserving the privacy of his search request and the contents of documents he retrieved.Several experiments have been conducted to illustrate the performance of our proposed methods. Furthermore deep analysis have been presented to prove the security of our methods.