Abstract:Cloud storage provides a convenient, massive,and scalable storage at low cost, but data privacy is a major concern thatprevents users from storing files on the cloud trustingly. One way of enhancingprivacy from data owner point of view is to encrypt the files beforeoutsourcing them onto the cloud and decrypt the files after downloading them.However, data encryption is a heavy overhead for the mobile devices, and dataretrieval process incurs a complicated communication between the data user andcloud. Normally with limited bandwidth capacity and limited battery life, theseissues introduce heavy overhead to computing and communication as well as ahigher power consumption for mobile device users, which makes the encryptedsearch over mobile cloud very challenging. In proposed system, we propose TEES(Traffic and Energy saving Encrypted Search), a bandwidth and energy efficientencrypted search architecture over mobile cloud. The proposed architectureoffloads the computation from mobile devices to the cloud, and we furtheroptimize the communication between the mobile clients and the cloud. It isdemonstrated that the data privacy does not degrade when the performanceenhancement methods are applied. Our experiments show that TEES reduces thecomputation time and save the energy consumption on file retrieval, meanwhilethe network traffics during the file retrievals are also significantly reduced.
Keywords:Sentiment analysis, Opinion mining, Product reviews, Natural languageprocessing.