Parallel Operations over TFHE-Encrypted Multi-Digit Integers

Jakub Klemsa, Melek Önen
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引用次数: 8

Abstract

Recent advances in Fully Homomorphic Encryption (FHE) allow for a practical evaluation of non-trivial functions over encrypted data. In particular, novel approaches for combining ciphertexts broadened the scope of prospective applications. However, for arithmetic circuits, the overall complexity grows with the desired precision and there is only a limited space for parallelization. In this paper, we put forward several methods for fully parallel addition of multi-digit integers encrypted with the TFHE scheme. Since these methods handle integers in a special representation, we also revisit the signum function, firstly addressed by Bourse et al., and we propose a method for the maximum of two numbers; both with particular respect to parallelization. On top of that, we outline an approach for multiplication by a known integer. According to our experiments, the fastest approach for parallel addition of 31-bit encrypted integers in an idealized setting with 32 threads is estimated to be more than 6x faster than the fastest sequential approach. Finally, we demonstrate our algorithms on an evaluation of a practical neural network.
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tfhe加密多位数整数的并行运算
完全同态加密(FHE)的最新进展允许对加密数据上的非平凡函数进行实际评估。特别是,结合密文的新方法拓宽了潜在应用的范围。然而,对于算术电路,整体的复杂性随着所需的精度而增长,并且只有有限的空间用于并行化。本文提出了几种用TFHE方案加密的多位数整数的完全并行加法的方法。由于这些方法以一种特殊的表示方式处理整数,我们也重新审视了sgn函数,首先由Bourse等人提出,我们提出了两个数的最大值的方法;都是关于并行化的。在此基础上,我们概述了一种与已知整数相乘的方法。根据我们的实验,在具有32个线程的理想设置中,并行添加31位加密整数的最快方法估计比最快的顺序方法快6倍以上。最后,我们在一个实际的神经网络评估上展示了我们的算法。
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Session details: Session 7: Encryption and Privacy RS-PKE: Ranked Searchable Public-Key Encryption for Cloud-Assisted Lightweight Platforms Prediction of Mobile App Privacy Preferences with User Profiles via Federated Learning Building a Commit-level Dataset of Real-world Vulnerabilities Shared Multi-Keyboard and Bilingual Datasets to Support Keystroke Dynamics Research
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