ENHANCING THE EFFICACY OF INEQUALITY QUERY AUDITING AND IMPROVED IN DEVIATION AUDITING USING CASTLE ALGORITHM

Abstract

We reconsider the various query auditing problem in set of sensitive data is outsourced to a cloud server. Castle query auditing scheme audits aggregate queries including sum, max, min, deviation, etc. These are submitted into an often manner, on the method to protect inference disclosure. It audits currently arrived queries on a single attribute, If any answering it may compromise any individual privacy that query will be rejected. This method analyzes risk of answering a query based on the query history. In additionally we propose relax CASTLE method for enhancing the utility by returning answers with slender perturbations. Our method can be applied into audit intermingled equality queries with extension. Experiments are conducted to evaluate the efficiency and effectiveness of our methods