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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed,Open Access and Multidisciplinary

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Ranked Query Support in Untrusted Cloud without Reveal Sensitive Data

B. Seetharamulu, Dr.G.V. Uma, , ,


Now-a-days Cloud computing is become more popular as cloud infrastructure for storing the data. Data owners are stored their data in public cloud for the flexibility and cost-preserving. In order to providing data privacy, Clouds allow users to store data and access can be made anywhere, any time by using any device. Highly sensitive information such as business documents, medical records and personal information may be stored in a cloud. Security and privacy are thus very important issues in cloud computing. To keep user data confidential from an untrusted Cloud Service Provider and third parties, a natural way is encryption. The data decryption key should be disclosed only to users who have been authorized. Users can search their files using keywords in the cloud. In existing literature many schemes have been proposed. In this paper, a new technique is described: Ranked Query support in Untrusted Cloud without Reveal Sensitive Data. Which performs operations on encrypted data which will provide results without decrypting that data? It provides privacy for user querying patterns and user data. It allows Cloud Service Providers to perform operations on the encrypted data. The Cloud Service Provider is unaware of the files and keywords stored in the cloud. Ranking is used for efficient and fast retrieval of the desired files. Ranks will be assigned to files based on the frequency of access of the files.

B. Seetharamulu,Dr.G.V. Uma."Ranked Query Support in Untrusted Cloud without Reveal Sensitive Data". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 05,pp.369-371, May- 2015, URL :,

Keywords : Cloud computing security, keyword search, Multidimensional Range Query, Random Space Encryption, consumer-centric cloud, Hybrid storage systems, and approximate queries.

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