加密整数除法和安全比较

T. Veugen
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引用次数: 54

摘要

在处理加密域中的数据时,可以使用同态加密对加密数据进行线性操作。但是,加密数据的整数除法需要客户端和服务器之间的附加协议,并且成本相对较高。利用同态加密和加性盲的方法对半诚实模型中的加密数据进行分割,具有较低的计算复杂度和通信复杂度。在我们的大多数协议中,我们假设除数是公开的。除法结果不仅可以精确计算,而且可以近似计算,从而进一步提高性能。将近似整数除法结果的思想扩展到客户机-服务器模型中的安全比较、安全最小值和安全最大值的类似结果,从而产生新的高效协议,并在生物识别学中得到了演示应用。精确的最小协议被证明优于现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Encrypted integer division and secure comparison
When processing data in the encrypted domain, homomorphic encryption can be used to enable linear operations on encrypted data. Integer division of encrypted data however requires an additional protocol between the client and the server and will be relatively expensive. We present new solutions for dividing encrypted data in the semi-honest model using homomorphic encryption and additive blinding, having low computational and communication complexity. In most of our protocols we assume the divisor is publicly known. The division result is not only computed exactly, but may also be approximated leading to further improved performance. The idea of approximating the result of an integer division is extended to similar results for secure comparison, secure minimum, and secure maximum in the client-server model, yielding new efficient protocols with demonstrated application in biometrics. The exact minimum protocol is shown to outperform existing approaches.
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