  Nowadays, huge amount of documents are increasingly transferred to the remote
servers due to the appealing features of cloud computing. On the other hand,
privacy and security of the sensitive information in untrusted cloud
environment is a big concern. To alleviate such concerns, encryption of
sensitive data before its transfer to the cloud has become an important risk
mitigation option. Encrypted storage provides protection at the expense of a
significant increase in the data management complexity. For effective
management, it is critical to provide efficient selective document retrieval
capability on the encrypted collection. In fact, considerable amount of
searchable symmetric encryption schemes have been designed in the literature to
achieve this task. However, with the emergence of big data everywhere,
available approaches are insufficient to address some crucial real-world
problems such as scalability.
  In this study, we focus on practical aspects of a secure keyword search
mechanism over encrypted data on a real cloud infrastructure. First, we propose
a provably secure distributed index along with a parallelizable retrieval
technique that can easily scale to big data. Second, we integrate authorization
into the search scheme to limit the information leakage in multi-user setting
where users are allowed to access only particular documents. Third, we offer
efficient updates on the distributed secure index. In addition, we conduct
extensive empirical analysis on a real dataset to illustrate the efficiency of
the proposed practical techniques.
