Data dynamics enabled privacy-preserving public batch auditing in cloud storage

Many schemes have been present to tackle data integrity and retrievability in cloud storage. Few of existing schemes support data dynamics, public verification and protect data privacy simultaneously. We propose a public auditing scheme which enables privacy-preserving, data dynamics and batch auditing. A data updating information table is designed to record the status information of the data blocks and facilitate data dynamics. Homomorphic authenticator and random masking technologies are exploited to protect data privacy for data owners. The scheme employs a Trusted third party auditor (TTPA) to verify the data integrity without learning any information about the data content during the auditing process. The scheme also allows batch auditing so that TTPA can process multiple auditing requests simultaneously which greatly accelerates the auditing process. Security and performance analysis show that our scheme is secure and feasible.