Abstract
Big graph model is frequently used to represent large-scale datasets such as geographical and healthcare data. Deploying these datasets in a third-party public cloud is a common solution for data sharing and processing. Maintaining data security in a public cloud is crucial. Here we target the data integrity issue, which is mainly achieved by hash operations. Existing hash schemes for graphs-structured data are either not suitable to all type of graphs or not computationally efficient for big graph. In this paper, we propose a secure, scalable hash scheme that is applicable to big graphs/trees, and its computation is highly efficient. We use the graph structure information to make our scheme unforgeable. Furthermore, we skillfully tune the scheme to make the graph verification and update processes very efficient. We will prove that our hash scheme is cryptographically secure. Our experimental results show that it has scalable computation performance.
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Acknowledgements
The authors would like to thank the U.S. NSF (National Science Foundation) for their support through the project DUE-1315328. Any ideas presented here do not necessarily represent NSF’s opinions.
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Lu, Y., Hu, F., Li, X. (2018). Towards the Security of Big Data: Building a Scalable Hash Scheme for Big Graph. In: Latifi, S. (eds) Information Technology - New Generations. Advances in Intelligent Systems and Computing, vol 558. Springer, Cham. https://doi.org/10.1007/978-3-319-54978-1_33
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DOI: https://doi.org/10.1007/978-3-319-54978-1_33
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