Outsourced data modification algorithm with assistance of multi-assistants in cloud computing

Abstract

The rapid development of cloud storage in these years has caused a wave of research craze. To improve the cloud user experience, a large amount of schemes are proposed with various practical performances, for instance, long term correct data storage and dynamic data modification. In most works, however, the authors seem to completely ignore the hard fact that data owner alone could not have enough energy to discover and correct all the inappropriate data outsourced in cloud. Others did consider it, and gave more than one user both read and write permissions, which leads to chaotic management of multiusers. In this paper, we propose a novel algorithm, in which the data owner and several authenticated assistants form a team to support dynamic data modification together. Assistants are in charge of detecting problems in cloud data and discussing a corresponding modification suggestion, while data owner is responsible for the implementation of the modification. In addition, our algorithm supports identity authentication, efficient malicious assistant revocation, as well as lazy update. Sufficient numerical analysis validates the performance of our algorithm.