A Multi-grained Log Auditing Scheme for Cloud Data Confidentiality
Zhen Yang, Wenyu Wang, Yongfeng Huang, Xing Li · Mobile Networks and Applications · 2019
Abstract With increasing number of cloud data leakage accidents exposed, outsourced data control becomes a more and more serious concern of their owner. To relieve the concern of these cloud users, reliable logging schemes are widely used to generate proof for data confidentiality auditing. However, high frequency operation and fine operation granularity on cloud data both result in a considerably large volume of operation logs, which burdens communication and computation in log auditing. This paper proposes a multi-grained log auditing scheme to make logs volume smaller and log auditing more efficient. We design a logging mechanism to support multi-grained data access with Merkle Hash Tree structure. Based on multi-grained log, we present a log auditing approach to achieve data confidentiality auditing and leakage investigation by making an Access List. Experiments results indicate that our scheme obtains about 54% log volume and 60% auditing time of fine-grained log auditing scheme in our scenario.