An efficient and secure privacy-preserving approach for outsourced data of resource constrained mobile devices in cloud computing

Abstract

Outsourcing of data into cloud has become an effective trend in modern day computing due to its ability to provide low-cost, pay-as-you-go IT services. Although cloud based services offer many advantages, privacy of the outsourced data is a big concern. To mitigate this concern, it is desirable to outsource sensitive data in an encrypted form but cost of encryption process would increase the heavy computational overhead on thin clients such as resource-constrained mobile devices. Recently, several keyword searchable encryption schemes have been described in the literature. However, these schemes are not effective for resource-constrained mobile devices, because the adopted encryption system should not only support keyword search over the encrypted data but also offer high performance. In this paper, we propose an efficient and secure privacy-preserving approach for outsourced data of resource-constrained mobile devices in the cloud computing. Our approach employs probabilistic public key encryption algorithm for encrypting the data and invoke ranked keyword search over the encrypted data to retrieve the files from the cloud. We aim to achieve an efficient system for data encryption without sacrificing the privacy of data. Further, our ranked keyword search greatly improves the system usability by enabling ranking based on relevance score for search result, sends top most relevant files instead of sending all files back, and ensures the file retrieval accuracy. As a result, data privacy ensures and computation, communication overheads in reduction. Thorough security and performance analysis, we prove that our approach is semantically secure and efficient.