Towards Practical Homomorphic Encryption in Cloud Computing

Adil Bouti, J. Keller
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引用次数: 11

Abstract

Secure computing in clouds faces many challenges related to data confidentiality and integrity. Classical security models focus on securing data from outside attacks, e.g. from other cloud users. Yet, breach of data confidentiality by the cloud provider has received far less attention. In previous work, we presented a protocol to delegate computations into clouds, providing security against other cloud users and cloud providers through encrypted data. The protocol is based on homomorphic properties of encryption algorithms. However,that protocol was only practical in certain circumstances. In the present paper we introduce some practical extensions to our algorithm to improve its efficiency. Additionally we extend the algorithm to support multiparty computation while preserving its homomorphic properties. We then show how these optimization blocks can be used for applying the scheme to efficient face recognition using Eigenface recognition algorithm.
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云计算中实用的同态加密
云中的安全计算面临着许多与数据机密性和完整性相关的挑战。传统的安全模型侧重于保护数据免受外部攻击,例如来自其他云用户的攻击。然而,云提供商违反数据保密性的行为受到的关注要少得多。在之前的工作中,我们提出了一种协议,将计算委托给云,通过加密数据提供针对其他云用户和云提供商的安全性。该协议基于加密算法的同态特性。但是,该议定书只在某些情况下是实用的。在本文中,我们引入了一些实用的扩展,以提高算法的效率。此外,我们扩展了该算法,使其在保持同态特性的同时支持多方计算。然后,我们展示了如何将这些优化块用于使用特征人脸识别算法将该方案应用于有效的人脸识别。
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