Public Integrity Auditing for Dynamic Data Sharing With Multiuser Modification

In past years, the rapid development of cloud storage services makes it easier than ever for cloud users to share data with each other. To ensure users' confidence of the integrity of their shared data on cloud, a number of techniques have been proposed for data integrity auditing with focuses on various practical features, e.g., the support of dynamic data, public integrity auditing, low communication/computational audit cost, and low storage overhead. However, most of these techniques consider that only the original data owner can modify the shared data, which limits these techniques to client read-only applications. Recently, a few attempts started considering more realistic scenarios by allowing multiple cloud users to modify data with integrity assurance. Nevertheless, these attempts are still far from practical due to the tremendous computational cost on cloud users, especially when high error detection probability is required by the system. In this paper, we propose a novel integrity auditing scheme for cloud data sharing services characterized by multiuser modification, public auditing, high error detection probability, efficient user revocation as well as practical computational/communication auditing performance. Our scheme can resist user impersonation attack, which is not considered in existing techniques that support multiuser modification. Batch auditing of multiple tasks is also efficiently supported in our scheme. Extensive experiments on Amazon EC2 cloud and different client devices (contemporary and mobile devices) show that our design allows the client to audit the integrity of a shared file with a constant computational cost of 340 ms on PC (4.6 s on mobile device) and a bounded communication cost of 77 kB for 99% error detection probability with data corruption rate of 1%.