Privacy-preserving public auditing for secure data storage in fog-to-cloud computing

With increasing popularity of fog-to-cloud based Internet of Things (IoT), how to ensure the integrity of IoT data outsourced in clouds has become one of the biggest security challenges. However, little effort has been put into addressing the problem. To fill this gap, this paper presents a tailor-made public auditing scheme for data storage in fog-to-cloud based IoT scenarios, which can achieve all indispensable performance and security requirements. Particularly, we design a tag-transforming strategy based on the bilinear mapping technique to convert the tags generated by mobile sinks to the ones created by the fog nodes in the phase of proof generation, which cannot only effectively protect the identity privacy, but also reduce the communication and computational costs in the verification phase; moreover, we present a zero-knowledge proof mechanism to verify the integrity of IoT data from various generators (e.g., mobile sinks and fog nodes) while achieving perfect data-privacy preserving. We formally prove the security of our scheme and evaluate its performance by theoretical analysis and comprehensive experiments. The results demonstrate that our scheme can efficiently achieve secure auditing for data storage in fog-to-cloud based IoT scenarios, and outperforms the straight-forward solution in communication and computational costs as well as energy consumption.