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The Design and Implementation of Multi-dimensional Bloom Filter Storage Matrix

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Network and System Security (NSS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9955))

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Abstract

Bloom filter is a bit array (a one-dimensional storage structure) that provides a compact representation for a set of data, which can be used to answer the membership query in an efficient manner with possible false positives. It has a lot of applications in many areas. In this paper, we further improve Bloom filter by proposing the use of multi-dimensional matrix to replace the one-dimensional structure. Based on our N-dimensional matrix structure, we propose four kinds of filter implementation, namely OFFF, ZFFF, WOFF, FFF (we refer it as Feng Filter). We prove that the false positive rate of our method is lower than the traditional one-dimensional Bloom filter. We also present the detailed implementation of our proposed filter. The traditional Bloom filter can be regarded as a special case of the Feng Filter.

This work is supported by Beijing Natural Science Foundation (4164089).

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Author information

Authors and Affiliations

  1. Law School, Renmin University of China, Beijing, China

    Fei Xu, Pinxin Liu, Jianfeng Yang & Jing Xu

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

    Fei Xu

Authors
  1. Fei Xu
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  2. Pinxin Liu
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  3. Jianfeng Yang
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  4. Jing Xu
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Corresponding author

Correspondence to Pinxin Liu .

Editor information

Editors and Affiliations

  1. Central China Normal University , Wuhan, China

    Jiageng Chen

  2. Università degli Studi di Milano , Crema (CR), Italy

    Vincenzo Piuri

  3. Osaka University , Osaka, Japan

    Chunhua Su

  4. Columbia University , New York, New York, USA

    Moti Yung

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© 2016 Springer International Publishing AG

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Xu, F., Liu, P., Yang, J., Xu, J. (2016). The Design and Implementation of Multi-dimensional Bloom Filter Storage Matrix. In: Chen, J., Piuri, V., Su, C., Yung, M. (eds) Network and System Security. NSS 2016. Lecture Notes in Computer Science(), vol 9955. Springer, Cham. https://doi.org/10.1007/978-3-319-46298-1_35

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  • DOI: https://doi.org/10.1007/978-3-319-46298-1_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46297-4

  • Online ISBN: 978-3-319-46298-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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