Enhanced and secure query services in cloud with perfect data privacy for the data owner

Abstract

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. It allows users to learn data from various different levels or angles, categorize it and summarize the associations identified. Increasing data intensity in cloud may also need to improve scalability and stability. Sensitive data must be preserved securely on violating the environment. This research work presents to secure the queries and to retrieve data to the client in an efficient manner. In this proposed work, two schemes, random space perturbation (RASP) and Advanced Encryption Standard (AES) are used for the purpose of initialization and to encrypt the data. Finally, Dijkstra’s algorithm is applied to calculate the distance between the nearby objects in the database. Comparing to K-NN, Dijkstra’s algorithm provides exact results, so its performance is highly accurate. In order to decrease the computational cost inherent to process the encrypted data, consider the case of incrementally updating datasets in the entire progress.