Efficient Pairing-Free Privacy-Preserving Auditing Scheme for Cloud Storage in Distributed Sensor Networks - Xinpeng Zhang; Chunxiang Xu; Xiaojun Zhang (International Journal of Distributed Sensor Networks)
With the rapid growth of the distributed sensor networks, the distributed sensor network data security problems begin to attract the attention of people. The previous research of distributed sensor network security has focused on secure information in communication; however the research of secure data storage has been overlooked. As we know, cloud data storage and retrieval have become popular for efficient data management in distributed sensor networks; thus they can enjoy the on-demand high-quality cloud storage service. Meanwhile, it also introduces new security challenges. To tackle with these security challenges, many classic auditing schemes of cloud storage have been proposed. However, these schemes all need very expensive pairing computation, which is not suitable for sensor networks. In this paper, we propose an efficient pairing-free auditing scheme for data storage of distributed sensor networks. We exploit homomorphic message authentication codes (MACs) to reduce the space used to store the verification information. We also employ the random masking technique to make sure the TPA cannot recover the primitive data blocks of the sensor networks data manager. Experimental results show that our auditing scheme is more light-weight than previous auditing schemes and more practical in applied distributed sensor networks environments.