Protecting business intelligence and customer privacy while outsourcing data mining tasks

作者:Ling Qiu, Yingjiu Li, Xintao Wu

摘要

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.

论文关键词:False Positive Rate, Hash Function, Association Rule, False Negative Rate, Storage Requirement

论文评审过程:

论文官网地址:https://doi.org/10.1007/s10115-007-0113-3