Efficient Audit Services for Data Outsourcing in Clouds

Abstract

This paper introduce a dynamic audit service for integrity verification of untrusted and outsourced storages. Our audit service is constructed based on the techniques, fragment structure, random sampling, and index-hash table, supporting provable updates to outsourced data and timely anomaly detection. Constructed on interactive proof system (IPS) with the zero knowledge property, our audit service can provide public auditability without downloading raw data and protect privacy of the data. Also, our audit system can support dynamic data operations and timely anomaly detection with the help of several effective techniques, such as fragment structure, random sampling, and index-hash table (IHT). We also propose an efficient approach based on probabilistic query and periodic verification for improving the performance of audit services. A proof-ofconcept prototype is also implemented to evaluate the feasibility and viability of our proposed approaches. Our experimental results not only validate the effectiveness of our approaches, but also show that our system does not create any significant computation cost and require less extra storage for integrity verification.