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A more well-founded security proof of the privacy-preserving distributed mining of association rules protocols

机译:关联规则协议的隐私保护分布式挖掘的更完善的安全性证明

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摘要

Privacy-preserving data mining aims at discovering beneficial information from a large amount of data without violating the privacy policy. Privacy-preserving association rules mining research has already generated many interesting results. Based on commutative encryptions and the Secure Multi-party Computation (SMC) theory, Kantarcioglu and Clifton [1] propose two protocols to implement privacy-preserving mining of association rules over horizontally partitioned data. The paper addresses its incorrect security proof and introduces a more well-founded proof. This paper also identifies several other errors in [1]. This kind of protocols and their proof are a concrete application of Secure Multi-party Computation, which is be of great significances to the privacy-preserving data mining studies based on SMC. Thus establishment of the correct proof methodology is important. This paper demonstrates the correct proof methodology by correcting the fault proof in [1]
机译:隐私保护数据挖掘的目的是在不违反隐私策略的情况下从大量数据中发现有益的信息。隐私保护关联规则挖掘研究已经产生了许多有趣的结果。基于可交换加密和安全多方计算(SMC)理论,Kantarcioglu和Clifton [1]提出了两种协议来实现对水平划分的数据的关联规则的隐私保护挖掘。该论文解决了其不正确的安全证明,并介绍了一个更有根据的证明。本文还确定了[1]中的其他几个错误。这种协议及其证明是安全多方计算的具体应用,对于基于SMC的隐私保护数据挖掘研究具有重要意义。因此,建立正确的证明方法很重要。本文通过纠正[1]中的故障证明来演示正确的证明方法。

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