Privacy-preserving Sorting Algorithms For Clouds

Data outsourcing is accepted by more and more companies and individuals due to its profits on low costs of resource configuration and maintenance.However,it makes owners losing their control of their owned data,which causes privacy-preserving problems of sensitive data.Data encryption is a common strategy for privacy preservation in clouds.The data generated by a symmetric encryption such as AES,DES,etc.,is useless for operation,which blunt the advantage of cloud computing.Sorting is a common operation in computer applications.It is a challenge to implement privacypreserving sorting over encrypted data without leaking plaintext.First we propose privacy-preserving sorting algorithms based on secure comparator.Secure comparator is constructed by PMV and HMAC techniques,which can be used to compare two data items without knowing their real values.Data owners firstly encrypt their data and generate the corresponding secure comparators and then outsource them into clouds.Cloud servers can sort the outsourced encrypted data according to their corresponding secure comparators by using the proposed privacy-preserving sorting algorithms.Then we propose privacy-preserving sorting algorithms based on logistic map.Comparable codes are constructed by logistic map functions for the corresponding encrypted data items comparison even without knowing their plaintext values.Data owners firstly encrypt their data and generate the corresponding comparable codes and then outsource them to clouds.Cloud servers sort the outsourced encrypted data in accordance with their comparable codes by the proposed privacypreserving sorting algorithms.Finally,experiment results show that the proposed privacy-preserving sorting algorithms based on secure comparator and privacy-preserving sorting algorithms based on logistic map both can protect data privacy while providing efficient sorting on encrypted data.