Abstract
Cloud computing has been in increasing concentration these years. Nevertheless, recently, it suffers the ambiguity in discerning responsibilities for unexpected incapable services. At this time, people refer to the logs. However, since logs may judge the fault, they are susceptible to malicious modification. Thus, their integrity is vital. Existing solutions leverage blockchain technology to tackle this problem, but few of them take the pseudo-anonymous nature of blockchain into considerations. This risks users’ privacy when they anchor their logs onto the blockchain. Some solutions try to be anonymous, but they are not general enough to be practical. In this paper, we propose a blockchain-based anonymous logging system for cloud environment. Our system introduces zero-knowledge proof to realize anonymous authentication, which can ensure undeniability in auditing while doing no harm to anonymity. Through experimental evaluation, we evaluate the feasibility and anonymity of the proposed system.
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
Chunqiang, H., Li, W., Cheng, X., Jiguo, Yu., Wang, S., Bie, R.: A secure and verifiable access control scheme for big data storage in clouds. IEEE Trans. Big Data 4(3), 341–355 (2018)
Liang, X., Shetty, S., Tosh, D., et al.: ProvChain: a blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability. In: IEEE/ACM International Symposium on Cluster (2017)
Ramachandran, A., Kantarcioglu, M.: SmartProvenance: a distributed, Blockchain based data provenance system. In: CODASPY (2018)
Pourmajidi, W., Miranskyy, A.: Logchain: blockchain-assisted log storage. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), San Francisco, CA, pp. 978–982 (2018)
Zhang, Y., Wu, S., Jin, B.: Du, J.: A blockchain-based process provenance for cloud forensics. In: 2017 3rd IEEE International Conference on Computer and Communications (ICCC), Chengdu, pp. 2470–2473 (2017)
Reid, F., Harrigan, M.: An analysis of anonymity in the Bitcoin system (2011)
Ermilov, D., Panov, M., Yanovich, Y.: Automatic bitcoin address clustering. In: 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA), Cancun, pp. 461–464 (2017)
Groth, J.: Short pairing-based non-interactive zero-knowledge arguments. In: Abe, M. (ed.) ASIACRYPT 2010. LNCS, vol. 6477, pp. 321–340. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17373-8_19
Lipmaa, H.: Progression-free sets and sublinear pairing-based non-interactive zero-knowledge arguments. In: Cramer, R. (ed.) TCC 2012. LNCS, vol. 7194, pp. 169–189. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28914-9_10
Sasson, E.B., Chiesa, A., Garman, C., et al.: Zerocash: decentralized anonymous payments from Bitcoin. In: Security & Privacy (2014)
Lei, X., Shah, N., Lin, C., et al.: Enabling the sharing economy: privacy respecting contract based on public blockchain. In: ACM Workshop on Blockchain (2017)
Chiesa, A., et al.: Cluster computing in zero knowledge. IACR Cryptology ePrint Archive (2015)
Díaz, C., Seys, S., Claessens, J., et al.: Towards measuring anonymity. In: International Conference on Privacy Enhancing Technologies (2002)
Shannon, C.E.: A mathematical theory of communication. Bell Labs Tech. J. 27(4), 379–423 (1948)
Eberhardt, J., Tai, S.: ZoKrates - scalable privacy-preserving off-chain computations. In: 2018 IEEE International Conference on Internet of Things (iThings), Halifax, NS, Canada, pp. 1084–1091 (2018)
Wang, J., Li, M., He, Y., Li, H., Xiao, K.: A blockchain based privacy-preserving incentive mechanism in crowdsensing applications. IEEE Access 6, 17545–17556 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Liu, JY., He, YH., Wang, C., Hu, Y., Li, H., Sun, LM. (2020). An Anonymous Blockchain-Based Logging System for Cloud Computing. In: Zheng, Z., Dai, HN., Tang, M., Chen, X. (eds) Blockchain and Trustworthy Systems. BlockSys 2019. Communications in Computer and Information Science, vol 1156. Springer, Singapore. https://doi.org/10.1007/978-981-15-2777-7_24
Download citation
DOI: https://doi.org/10.1007/978-981-15-2777-7_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-2776-0
Online ISBN: 978-981-15-2777-7
eBook Packages: Computer ScienceComputer Science (R0)