Privacy Preserving Third Party Auditing in Multi Cloud Storage Environment

Abstract

The on-demand, pay-per-use, and scalable services provided in cloud model guarantee to reduce capital as well as running expenditures for both hardware and software. In cloud environment, users can remotely store their data and access them from a shared pool of configurable computing resources, without local data storage burden. We discuss various methods related to the security and privacy capabilities in cloud paradigm especially data storage in multi cloud environment. We provide three models in form of multicloud architectures which allow categorizing the schemes and analyze them according to their security benefits. The different methods include, resource replication, split application system into tiers based on PIR methods, split both application logic and data into segments. In addition, since the integrity protection of data is a fearsome task in Cloud computing for users with limited computing resources, vulnerabilities in user data privacy are also possible in third party auditing. So we propose a safe cloud storage methodology which supports privacy-preserving third party auditing. And we study the outcomes to perform audits concurrently for multiple users in an efficient manner. Experimental results show that the third party auditing computation time is better than existing approach.