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Differentially Private Real-Time Streaming Data Publication Based on Sliding Window Under Exponential Decay

Lan Sun1, Chen Ge1, Xin Huang1, Yingjie Wu1,*, Yan Gao2

College of Mathematics and Computer Science, Fuzhou University, Xue Yuan Road, No. 2, Fuzhou, 350116, China.
Amazon, 410 Terry Avenue North, Seattle, Washington, 98109, USA.

* Corresponding Author: Yingjie Wu. Email: email.

Computers, Materials & Continua 2019, 58(1), 61-78. https://doi.org/10.32604/cmc.2019.03744

Abstract

Continuous response of range query on steaming data provides useful information for many practical applications as well as the risk of privacy disclosure. The existing research on differential privacy streaming data publication mostly pay close attention to boosting query accuracy, but pay less attention to query efficiency, and ignore the effect of timeliness on data weight. In this paper, we propose an effective algorithm of differential privacy streaming data publication under exponential decay mode. Firstly, by introducing the Fenwick tree to divide and reorganize data items in the stream, we achieve a constant time complexity for inserting a new item and getting the prefix sum. Meanwhile, we achieve time complicity linear to the number of data item for building a tree. After that, we use the advantage of matrix mechanism to deal with relevant queries and reduce the global sensitivity. In addition, we choose proper diagonal matrix further improve the range query accuracy. Finally, considering about exponential decay, every data item is weighted by the decay factor. By putting the Fenwick tree and matrix optimization together, we present complete algorithm for differentiate private real-time streaming data publication. The experiment is designed to compare the algorithm in this paper with similar algorithms for streaming data release in exponential decay. Experimental results show that the algorithm in this paper effectively improve the query efficiency while ensuring the quality of the query.

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APA Style
Sun, L., Ge, C., Huang, X., Wu, Y., Gao, Y. (2019). Differentially private real-time streaming data publication based on sliding window under exponential decay. Computers, Materials & Continua, 58(1), 61-78. https://doi.org/10.32604/cmc.2019.03744
Vancouver Style
Sun L, Ge C, Huang X, Wu Y, Gao Y. Differentially private real-time streaming data publication based on sliding window under exponential decay. Comput Mater Contin. 2019;58(1):61-78 https://doi.org/10.32604/cmc.2019.03744
IEEE Style
L. Sun, C. Ge, X. Huang, Y. Wu, and Y. Gao, “Differentially Private Real-Time Streaming Data Publication Based on Sliding Window Under Exponential Decay,” Comput. Mater. Contin., vol. 58, no. 1, pp. 61-78, 2019. https://doi.org/10.32604/cmc.2019.03744

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cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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