@article{scholars10460,
           title = {Data Privacy Protection Mechanisms in Cloud},
            note = {cited By 26},
          volume = {3},
          number = {1},
             doi = {10.1007/s41019-017-0046-0},
         journal = {Data Science and Engineering},
       publisher = {Springer Science and Business Media Deutschland GmbH},
           pages = {24--39},
            year = {2018},
            issn = {23641185},
          author = {Singh, N. and Singh, A. K.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062713214&doi=10.1007\%2fs41019-017-0046-0&partnerID=40&md5=40d408ded1ded96f5fbbdedcb98a9152},
        abstract = {In the cloud computing environment, the privacy of the electronic data is a serious issue that requires special considerations. We have presented a state-of-the-art review of the methodologies and approaches that are currently being used to cope with the significant issue of privacy. We have categorized the privacy-preserving approaches into four categories, i.e., privacy by cryptography, privacy by probability, privacy by anonymization and privacy by ranking. Moreover, we have developed taxonomy of the techniques that have been used to preserve the privacy of the governing data. We also presented a comprehensive comparison of the privacy-preserving approaches from the angle of the privacy-preserving requirements{\^a}?? satisfaction. Therefore, it is highly desirable that the mechanisms should be developed to deploy efficient auditing and accountability mechanisms that anonymously monitor the utilization of data records and track the provenance to ensure the confidentiality of the data. {\^A}{\copyright} 2017, The Author(s).}
}