Secure multi-party computation in differential private data with Data Integrity Protection

Abstract

Secure multiparty computation (SMC) is needed now-a-days in which data are distributed between different parties. Moreover, organizations are wished to collaborate with other parties who conduct same business, for their mutual benefits. SMC provides users to gain much information from the larger data without disclosing the data. This project combines the technique secure multi-party computation and the differential privacy for vertically partitioned data between parties. To achieve this, a multi-party protocol has been proposed for the exponential mechanism. Reliable access to data is must for most computer applications and data servers. Some factors causes unauthorized access to stored data. Two Phase Validation (2PV) provides the authentication for the users, while integrating the data in multiparty computation. Data can get corrupted due to some malfunctions. Disk errors are common today but the storage technologies are not designed to handle such kind of errors. A simple integrity violation is detected by the higher level software which causes further loss of data. The proposed system is to verify the integrity of random subsets of data against general or malicious corruptions through Distributed Data Integrity (DDI) Protection.