PEGASUS: Bridging Polynomial and Non-polynomial Evaluations in Homomorphic Encryption

Wen-jie Lu, Zhicong Huang, Cheng Hong, Yiping Ma, Hunter Qu
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引用次数: 46

Abstract

Homomorphic encryption (HE) is considered as one of the most important primitives for privacy-preserving applications. However, an efficient approach to evaluate both polynomial and non-polynomial functions on encrypted data is still absent, which hinders the deployment of HE to real-life applications. To address this issue, we propose a practical framework PEGASUS. PEGASUS can efficiently switch back and forth between a packed CKKS ciphertext and FHEW ciphertexts without decryption, allowing us to evaluate arithmetic functions efficiently on the CKKS side, and to evaluate look-up tables on FHEW ciphertexts. Our FHEW → CKKS conversion algorithm is more practical than the existing methods. We improve the computational complexity from linear to sublinear. Moreover, the size of our conversion key is significantly smaller, e.g., reduced from 80 gigabytes to 12 megabytes. We present extensive benchmarks of PEGASUS, including sigmoid/ReLU/min/max/division, sorting and max-pooling. To further demonstrate the capability of PEGASUS, we developed two more applications. The first one is a private decision tree evaluation whose communication cost is about two orders of magnitude smaller than the previous HE-based approaches. The second one is a secure K-means clustering that is able to run on thousands of encrypted samples in minutes that outperforms the best existing system by 14 × – 20×. To the best of our knowledge, this is the first work that supports practical K-means clustering using HE in a single server setting.
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PEGASUS:同态加密中的桥接多项式和非多项式计算
同态加密(HE)被认为是隐私保护应用程序中最重要的原语之一。然而,目前仍然缺乏一种有效的方法来评估加密数据上的多项式和非多项式函数,这阻碍了HE在实际应用中的部署。为了解决这个问题,我们提出了一个实用的框架PEGASUS。PEGASUS可以在没有解密的情况下在打包的CKKS密文和FHEW密文之间有效地来回切换,允许我们在CKKS端有效地评估算术函数,并在FHEW密文上评估查找表。我们的FHEW→CKKS转换算法比现有的方法更实用。我们提高了从线性到次线性的计算复杂度。此外,我们的转换密钥的大小明显更小,例如,从80千兆字节减少到12兆字节。我们提供了PEGASUS的广泛基准测试,包括sigmoid/ReLU/min/max/division,排序和最大池。为了进一步展示PEGASUS的能力,我们开发了另外两个应用程序。第一种方法是一个私有决策树评估,其通信成本比之前基于he的方法小两个数量级。第二种是安全的K-means聚类,它能够在几分钟内运行数千个加密样本,比现有最好的系统性能高出14倍到20倍。据我们所知,这是第一个在单个服务器设置中使用HE支持实际K-means集群的工作。
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