Enhancing Privacy-Preserving Cloud Database Querying by Preventing Brute Force Attacks

Considering the complexities involved in Cloud computing, there are still plenty of issues that affect the privacy of data in cloud environment. Unless these problems get solved, we think that the problem of preserving privacy in cloud databases is still open. In tokenization and homomorphic cryptography based solutions for privacy preserving cloud database querying, there is possibility that by colluding with service provider adversary may run brute force attacks that will reveal the attribute values. In this paper we propose a solution by defining the variant of K – means clustering algorithm that effectively detects such brute force attacks and enhances privacy of cloud database querying by preventing this attacks. Keywords—Privacy, Database, Cloud Computing, Clustering, Kmeans, Cryptography.