Selecting key generating elliptic curves for Privacy Preserving Association Rule Mining (PPARM)

Amiruddin, R. F. Sari
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引用次数: 3

Abstract

Privacy Preservation in Data Mining (PPDM) including for Privacy Preserving Association Rule Mining (PPARM) has attracted lots of attention in recent research and practice. However, the current method or approach still have drawbacks in the sense that there are trade-offs between efficiency and privacy preservation. This paper describes our work towards providing a new efficient PPARM protocol. We reviewed current literature on PPARM and mapped the methods or approaches involved. As previous research showed that Elliptic Curve Cryptography (ECC) perform better than the other Public Key systems such as RSA and Diffie-Hellman, we will utilize ECC for reducing the computational cost of the new PPARM protocol. In choosing good elliptic curves for ECC, we measured the running time of the key generation for various group of recommended elliptic curves i.e. Brainpool curves (by Brainpool), Prime, C2pnb, C2tnb curves (by ANSI X9.62), Secp curves (by SECG), and PrimeCurve curves (by CDC Group). As the result, Secp curves outperformed all of the other curves on overall average ratio of running time and key size of key generation by 4.4% up to 357.6%.
隐私保护关联规则挖掘(PPARM)中密钥生成椭圆曲线的选择
数据挖掘中的隐私保护(PPDM)包括隐私保护关联规则挖掘(PPARM)在近年来的研究和实践中受到了广泛的关注。然而,目前的方法或方法仍然存在缺点,因为在效率和隐私保护之间存在权衡。本文描述了我们为提供一种新的高效的PPARM协议所做的工作。我们回顾了目前关于PPARM的文献,并绘制了所涉及的方法或途径。由于之前的研究表明椭圆曲线加密(ECC)比其他公钥系统(如RSA和Diffie-Hellman)性能更好,我们将利用ECC来降低新的PPARM协议的计算成本。在为ECC选择好的椭圆曲线时,我们测量了各种推荐椭圆曲线组的密钥生成运行时间,即Brainpool曲线(Brainpool), Prime, C2pnb, C2tnb曲线(ANSI X9.62), Secp曲线(SECG)和PrimeCurve曲线(CDC group)。结果表明,Secp曲线在运行时间和密钥生成大小的总体平均比率上优于所有其他曲线,最高为357.6%,最高为4.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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