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User Similarity-Aware Data Deduplication Scheme for IoT Applications

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Frontiers in Cyber Security (FCS 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1286))

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Abstract

As an important technology in cloud storage, deduplication is widely used to reserve network bandwidth and storage resources. While deduplication brings us convenience, there are also security risks that we have to confront. If internal data from organizations are treated in the same way of ordinary data, deduplication may lead to unexpected data leakage and other issues. A user similarity-aware data deduplication algorithm is proposed which can properly handle internal data uploaded by group users. This scheme can recognize the situation that uploaders with similar attributes hold the same data in the process of deduplication. The goal of our scheme is to ensure that the participation of group users will not change the current popularity of uploaded data. In the aspect of attribute distance calculation, we divide attribute types and introduce specific attribute distance calculation methods for each type. We determine user category by comparing the similarities of their attributes. Finally, the counting method of uploaded data is adjusted adaptively according to the current popularity status of data and user categories. This scheme can avoid potential internal data leakage caused by deduplication. Through experiment evaluation, we show that our scheme is efficient, and is of great scalability and practicability.

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Author information

Authors and Affiliations

  1. Qingdao University, Qingdao, 266071, China

    Yuan Gao, Hequn Xian & Yan Teng

  2. State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Yuan Gao & Hequn Xian

Authors
  1. Yuan Gao
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  2. Hequn Xian
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  3. Yan Teng
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Corresponding author

Correspondence to Hequn Xian .

Editor information

Editors and Affiliations

  1. Tianjin University, Tianjin, China

    Guangquan Xu

  2. Delft University of Technology, Delft, The Netherlands

    Kaitai Liang

  3. University of Aizu, Aizuwakamatsu, Japan

    Chunhua Su

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Gao, Y., Xian, H., Teng, Y. (2020). User Similarity-Aware Data Deduplication Scheme for IoT Applications. In: Xu, G., Liang, K., Su, C. (eds) Frontiers in Cyber Security. FCS 2020. Communications in Computer and Information Science, vol 1286. Springer, Singapore. https://doi.org/10.1007/978-981-15-9739-8_4

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  • DOI: https://doi.org/10.1007/978-981-15-9739-8_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-9738-1

  • Online ISBN: 978-981-15-9739-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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