Abstract
AbstractWith 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.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Information Systems,Software
Reference21 articles.
1. Ahsan MM, Wahab AWA, Idris MYI, Khan S, Bachura E, Choo KKR (2018) Class: cloud log assuring soundness and secrecy scheme for cloud forensics. IEEE Trans Sustain Comput
2. Chen Z, Tian H, Lu J, Nan F, Cai Y, Wang T, Chen Y (2017) Secure logging and public audit for operation behavior in cloud storage. In: 2017 IEEE international conference on computational science and engineering (CSE) and embedded and ubiquitous computing (EUC), vol 1. IEEE, pp 444–450
3. Cheng R, Xu R, Tang X, Sheng VS, Cai C (2018) An abnormal network flow feature sequence prediction approach for ddos attacks detection in big data environment. Comput Mater Continua 55(1):095–119
4. Li C, Hu J, Zhou K, Wang Y, Deng H (2018) Using blockchain for data auditing in cloud storage. In: International conference on cloud computing and security. Springer, pp 335–345
5. Liu Y, Peng H, Wang J (2018) Verifiable diversity ranking search over encrypted outsourced data. Comput Mater Continua 55(1):037–057
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