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Protecting business intelligence and customer privacy while outsourcing data mining tasks

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Abstract

Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the storage requirement.

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Authors and Affiliations

  1. School of Mathematics, Physics and Information Technology, James Cook University, Townsville, QLD, 4811, Australia

    Ling Qiu

  2. School of Information Systems, Singapore Management University, Singapore, 178902, Singapore

    Yingjiu Li

  3. Department of Software and Information Systems, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA

    Xintao Wu

Authors
  1. Ling Qiu
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  2. Yingjiu Li
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  3. Xintao Wu
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Corresponding author

Correspondence to Ling Qiu.

Additional information

This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.

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Qiu, L., Li, Y. & Wu, X. Protecting business intelligence and customer privacy while outsourcing data mining tasks. Knowl Inf Syst 17, 99–120 (2008). https://doi.org/10.1007/s10115-007-0113-3

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  • DOI: https://doi.org/10.1007/s10115-007-0113-3

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