Present State of the Art on Secure Data Deduplication in Cloud

Abstract

AbstractCloud is resource-rich distributed environment for outsourcing data and computations in pay as you go fashion. Organizations changed their business models with respect to computing resources. Different kinds of data are being outsourced to public cloud. The data also includes imagery that is essential in different real-world applications. However, providing privacy and security to the storage data is indispensable. From the cloud infrastructure point of view, it is essential to have provision for identifying duplicates in the objects stored and there needs to be a mechanism for secure deduplication. Deduplication at different levels of granularity is essential for improving performance of cloud infrastructure and also see that the privacy and security of data is not lost. The traditional methods used for deduplication do not work directly on the encrypted data. This has been overcome with certain deduplication methods that can act directly on the encrypted and outsourced data. The conventional cryptographic methods such as symmetric and asymmetric are not flexible to have flexibility in access control. Compressive sensing-based simultaneous data compression and security for data deduplication in cloud is the proposition desired. Toward this end, this paper reviews literature and find current academic thinking on this area of research. It covers various kinds of methods and provides valuable insights that help in further research in the area of secure storage of images in cloud in such a way that the deduplication process can be leveraged.KeywordsCloud computingData securityPrivacyDeduplicationEncryptionDecryptionCompression