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New packing method in somewhat homomorphic encryption and its applications href='#sec1164-note-1000'/>

机译:同态加密中的新打包方法及其应用 href =“#sec1164-note-1000” />

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Somewhat homomorphic encryption is public key encryption supporting a limited number of additions and multiplications on encrypted data. This encryption gives a powerful tool in performing meaningful computations with protecting data confidentiality, whose property is suitable mainly in cloud computing. In this paper, we focus on the scheme proposed by Brakerski and Vaikuntanathan, and present two types of packed ciphertexts in order to improve performance and reduce size of the encrypted data. One type of our packed ciphertexts is based on the message encoding technique proposed by Lauter, Naehrig and Vaikuntanathan. While their technique empowers efficient secure computation of sums and products over the integers, our second type of packed ciphertexts enables efficient secure computation of more complex functionalities such as multiple inner products and multiple Hamming distances. We apply our packing method to construct several protocols for secure biometric authentication and secure pattern matching computations. Our implementation shows that our method gives faster performance than the state‐of‐the‐art work in such applications. Copyright ? 2015 John Wiley & Sons, Ltd. New packing method in somewhat homomorphic encryption and its applications Masaya Yasuda, Takeshi Shimoyama, Jun Kogure, Kazuhiro Yokoyama and Takeshi Koshiba The figure shows an overview of our secure protocol for privacy‐preserving biometric authentication by homomorphic encryption.
机译:某种同态加密是公钥加密,它支持对加密数据进行有限数量的加法和乘法。这种加密为保护数据的机密性提供了执行有意义的计算的强大工具,其属性主要适用于云计算。在本文中,我们将重点放在Brakerski和Vaikuntanathan提出的方案上,并提出两种类型的压缩密文,以提高性能并减小加密数据的大小。我们打包密文的一种类型是基于Lauter,Naehrig和Vaikuntanathan提出的消息编码技术。尽管他们的技术可以对整数中的和与乘积进行有效的安全计算,但是我们的第二种压缩密文类型却可以对更复杂的功能(例如多个内积和多个汉明距离)进行有效的安全计算。我们将打包方法应用于安全生物特征认证和安全模式匹配计算的几种协议。我们的实现表明,与此类应用程序中的最新技术相比,我们的方法可提供更快的性能。版权? 2015 John Wiley&Sons,Ltd. 某种形式的同态加密的新打包方法及其应用Masaya Yasuda,Yoshishi Shimoyama,Jun Kogure,Kazuhiro Yokoyama和Takeshi Koshiba该图概述了我们用于保护隐私的生物特征认证的安全协议的概述。通过同态加密

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