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On-Demand Allocation of Cryptographic Computing Resource with Load Prediction

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Information and Communications Security (ICICS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14252))

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Abstract

“Cryptography-as-a-Service” provides convenience for users to request cryptographic computing resources according to their needs. However, it also brings challenges for resource management, such as the constantly changing load, large numbers of users, and complex resource topologies. To address those issues, this paper proposes a load-predicted-based resource allocation algorithm for cryptographic computing resources. Firstly, we propose a load-based cryptographic computing resource allocation model that can clearly describe the dynamic status of resources. Then, we design a load predictor using time series analysis and a random forest model, which can quickly predict the load of cryptography service requests during service time. Finally, we develop a load-predicted-based greedy algorithm for cryptographic computing resource allocation. Experimental results show that energy consumption is reduced by about 20% at most compared to the baseline allocation algorithm.

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Acknowledgements

This research is supported by National Key Research and Development Program of China (No. 2019YFB2101700).

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Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Xiaogang Cao, Fenghua Li, Kui Geng, Yingke Xie & Wenlong Kou

  2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China

    Xiaogang Cao & Fenghua Li

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  1. Xiaogang Cao
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  2. Fenghua Li
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  3. Kui Geng
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  4. Yingke Xie
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Correspondence to Wenlong Kou .

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Editors and Affiliations

  1. Nankai University, Tianjin, China

    Ding Wang

  2. Columbia University, New York, NY, USA

    Moti Yung

  3. Nankai University, Tianjin, China

    Zheli Liu

  4. Xidian University, Xi’an, China

    Xiaofeng Chen

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Cao, X., Li, F., Geng, K., Xie, Y., Kou, W. (2023). On-Demand Allocation of Cryptographic Computing Resource with Load Prediction. In: Wang, D., Yung, M., Liu, Z., Chen, X. (eds) Information and Communications Security. ICICS 2023. Lecture Notes in Computer Science, vol 14252. Springer, Singapore. https://doi.org/10.1007/978-981-99-7356-9_11

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  • DOI: https://doi.org/10.1007/978-981-99-7356-9_11

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  • Online ISBN: 978-981-99-7356-9

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