On the (In)Security and (Im)Practicality of Outsourcing Precise Association Rule Mining

Ian Molloy, Ninghui Li, Tiancheng Li
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引用次数: 58

Abstract

The recent interest in outsourcing IT services onto the cloud raises two main concerns: security and cost. One task that could be outsourced is data mining. In VLDB 2007, Wong et al. propose an approach for outsourcing association rule mining. Their approach maps a set of real items into a set of pseudo items, then maps each transaction non-deterministically. This paper, analyzes both the security and costs associated with outsourcing association rule mining. We show how to break the encoding scheme from Wong et al. without using context specific information and reduce the security to a one-to-one mapping. We present a stricter notion of security than used by Wong et al., and then consider the practicality of outsourcing association rule mining. Our results indicate that outsourcing association rule mining may not be practical, if the data owner is concerned with data confidentiality.
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论外包精确关联规则挖掘的安全性和实用性
最近对将IT服务外包到云上的兴趣引起了两个主要问题:安全性和成本。一个可以外包的任务是数据挖掘。在VLDB 2007中,Wong等人提出了一种外包关联规则挖掘的方法。他们的方法将一组真实项目映射到一组伪项目,然后不确定地映射每个事务。本文分析了外包关联规则挖掘的安全性和成本。我们展示了如何在不使用上下文特定信息的情况下破解Wong等人的编码方案,并将安全性降低到一对一映射。我们提出了一个比Wong等人使用的更严格的安全概念,然后考虑外包关联规则挖掘的实用性。我们的研究结果表明,如果数据所有者关心数据的机密性,那么外包关联规则挖掘可能不实用。
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