Shamir's key based confidentiality on cloud data storage

Confidentiality is used on accessing the set of cloud database information with high security level. The conventional encryption and decryption mechanism for the privacy maintenance in cloud zone acquire additional processing time. Hence, the cloud service did not explore effective confidentiality on information retrieval process. A new key distribution scheme for efficient privacy preserving query plans on the cloud data achieves a higher percentage of confidentiality by residing the cloud data with polynomial interpolation. To ensure high confidentiality and providing privacy to the cloud users the Shamir's Key Distribution based Confidentiality (SKDC) scheme is employed. SKDC scheme generates a polynomial of degree with the secret as the first coefficient and the remaining coefficients picked up at random to improve the privacy preserving level on the cloud infrastructure. Shamir's Key Distribution supports batch auditing where multiple user requests for data auditing is held concurrently at a higher confidentiality rate. SKDC scheme handles query processing using the matrix-structure form. An Experimental evaluation is performed with Amazon Simple Storage Service dataset to evaluate the confidentiality and privacy performance with Shamir's Key Distribution based Confidentiality (SKDC) scheme is compared with two well-known privacy schemes such as Trusted Third Party Model (TTPM) and Trusted Hardware Based Database. As a result, the SKDC scheme increases confidentiality level of the user by 22 % as compared to existing TTPM method.