Abstract
Since the cloud computation auditing becomes important recently, Wei et al. proposed their cloud computation auditing scheme. However, they assume that the cheating adversary always gives the random response for the auditing challenges. This assumption is impractical. When only a small part of adversary’s response is random, the number of challenges is increased dramatically. Then the auditing load becomes so heavy that the auditor cannot give the auditing results in reasonable time. Moreover, the probability of finding out incorrect computed results cannot reach that the users want. To improve the on-line audit performance or probability, the off-line easy-auditor improving strategy, the function-based improving strategy, and mixed strategy are proposed, respectively. Utilizing the off-line computation concept and the cloud computation server help, the online audit performance, and the audit probability will be improved.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang, B., Li, B., Li, H.: Knox: privacy-preserving auditing for shared data with large groups in the cloud. In: Applied Cryptography and Network Security, ACNS 2012. LNCS, vol. 7341, pp. 507–525. Springer, Heidelberg (2012)
Wang, B., Li, B., Li, H.: Oruta: Privacy-Preserving Auditing for Shared Data in the Cloud. In: Proceeding of IEEE 5th International Conference on Cloud Computing, IEEE Cloud 2012, pp. 295–302, Honolulu, HI, U.S.A, 24–29 June 2012
Wang, B., Li, B., Li, H.: Privacy-preserving public auditing for shared cloud data supporting group dynamics. In: Proceeding of IEEE International Conference on Communications, ICC 2013, pp. 1946–1950, Budapest, Hungary, 9–13 June 2013
Wang, C., Ren, K., Lou, W., Li, J.: Toward public auditable secure cloud data storage services. IEEE Netw. 24(4), 19–24 (2010)
Wang, Q., Wang, C., Ren, K., Lou, W., Li, J.: Enabling public auditability and data dynamics for storage security in cloud computing. In: Proceeding of ESORICS 2009, Saint Malo, France, 21–25 September 2009, pp. 355–370 (2009)
Belenkiy, M., Chase, M., Erway, C., Jannotti, J., Küpçü, A., Lysyanskaya, A.: Incentivizing outsourced computation. In: Proceedings of the 3rd International Workshop on Economics of Networked Systems, pp. 85–90, Seattle, WA, U.S.A, 17–22 August 2008
Canetti, R., Riva, B., Rothblum, G.: Verifiable computation with two or more clouds. In: Workshop on Cryptography and Security in Clouds, Zurich, Switzerland, 15–16 March 2011
Gennaro, R., Gentry, C., Parno, B.: Non-interactive verifiable computing: outsourcing computation to untrusted workers. In: 30th International Cryptology Conference, CYPTO 2010, pp. 465–482, Santa Barbara, California, U.S.A, 15–19 August 2010
Golle, P., Mironov, I.: Uncheatable distributed computations. In: The Cryptographers’ Track at RSA Conference 2001, pp. 425–440, San Francisco, CA, U.S.A, 8–12 April 2001
Sadeghi, A., Schneider, T., Winandy, M.: Token-based cloud computing: secure outsourcing of data and arbitrary computations with lower latency. In: Trust and Trustworthy Computing, pp. 417–429, Berlin, Germany, 21–23 June 2010
Wang, Q., Wang, C., Ren, K., Lou, W., Li, J.: Enabling public auditability and data dynamics for storage security in cloud computing. IEEE Trans. Parallel Distrib. Syst. 22(5), 847–859 (2012)
Wei, L., Zhu, H., Cao, Z., Jia, W., Vasilakos, A.: Seccloud: bridging secure storage and computation in cloud. In: 30th International Conference on Distributed Computing Systems Workshops, IEEE ICDCSW 2010, Genova, Italy, 21–25 June 2010
Wei, L., Zhu, H., Cao, Z., Jia, W., Dong, X., Jia, W., Chen, Y., Vasilakos, A.: Security and privacy for storage and computation in cloud computing. Inf. Sci. 258, 371–386 (2014)
Monrose, F., Wycko, P., Rubin, A.: Distributed execution with remote audit. In: Proceedings of the Network and Distributed Systems Security Symposium (NDSS), San Diego, California, U.S.A, pp. 103–113 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Hwang, SJ., Li, TL. (2018). Strategies to Improve Auditing Performance and Soundness for Cloud Computation. In: Peng, SL., Wang, SJ., Balas, V., Zhao, M. (eds) Security with Intelligent Computing and Big-data Services. SICBS 2017. Advances in Intelligent Systems and Computing, vol 733. Springer, Cham. https://doi.org/10.1007/978-3-319-76451-1_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-76451-1_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-76450-4
Online ISBN: 978-3-319-76451-1
eBook Packages: EngineeringEngineering (R0)