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基于paillier的隐私保护下关联规则挖掘方法.. 被引量:1

Privacy-preserving mining of association rules based on paillier encryption algorithm
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摘要 在基于隐私保护的数据挖掘中,挖掘的精度和安全性一直是一对矛盾,针对该矛盾提出了一种在分布式的环境下基于paillier同态加密的关联规则挖掘方法,该方法将计算方和解密方分离保证了数据挖掘的安全性,同时基于同态加密并不会影响挖掘的精度,并通过蒙哥马利算法降低了paillier算法的开销,经过实验发现在增加加解密过程后算法开销还是在能接受的范畴内。 In privacy preserving association rule mining, the precision and security of mining are always a pair of contradictions. A method of privacy-preserving mining of association rules based on paillier encryption algorithm over distributed databases was proposed. The method separated calculation and decryption so it can solve the prob- lem of accuracy and security from mining of association rules perfectly. The method can reduce the time cost by Montgomery reduction. The experiment shows that the time cost on the basis of adding the process of encryption and decryption is acceptable.
作者 邢欢 张琳
出处 《网络与信息安全学报》 2016年第1期53-59,共7页 Chinese Journal of Network and Information Security
基金 国家自然科学基金资助项目(No.61402241) 江苏省自然科学基金资助项目(No.BK2012436) 省属高校自然科学研究重大基金资助项目(No.12KJA520002 No.14KJA520002) 江苏省高校自然科学基金资助项目(No.13KJB520017)~~
关键词 隐私保护 关联规则 同态加密 privacy preserving, association rules, homomorphic encryption
作者简介 邢欢(1991.),男,江苏启东人,南京邮电大学硕士生,主要研究方向为分布式计算、数据挖掘、隐私保护等。 通信作者:张琳,zhangl@niupt.edu.cn 张琳(1980-),女,江苏丰县人,博士后,南京邮电大学副教授、硕士生导师,主要研究方向为分布式计算、网络安全、隐私保护等。
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