Falcon: Fast Spectral Inference on Encrypted Data
Authors: Qian Lou, Wen-jie Lu, Cheng Hong, Lei Jiang
NeurIPS 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results show Falcon achieves the state-of-the-art inference accuracy and reduces the inference latency by 45.45% 85.34% over prior HENNs on MNIST and CIFAR-10. |
| Researcher Affiliation | Collaboration | Qian Lou Indiana University Bloomington louqian@iu.edu; Wen-jie Lu Alibaba Group juhou.lwj@alibaba-inc.com; Cheng Hong Alibaba Group vince.hc@alibaba-inc.com; Lei Jiang Indiana University Bloomington jiang60@iu.edu |
| Pseudocode | Yes | Algorithm 1: Homomorphic DFT (HDFT).; Algorithm 2: Homomorphic FC Layer (HFC).; Algorithm 3: Homomorphic Convolutional Layer. |
| Open Source Code | No | The paper does not include an unambiguous statement about releasing the source code for the methodology described, nor does it provide a direct link to a code repository. |
| Open Datasets | Yes | Our datasets include MNIST [18] and CIFAR-10 [19].; [18] Yann Le Cun, Corinna Cortes, and CJ Burges. MNIST Handwritten Digit Database. AT&T Labs [Online]. Available: http://yann.lecun.com/exdb/mnist, 2010.; [19] Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The cifar-10 dataset, 2014. http://www.cs.toronto.edu/kriz/cifar.html. |
| Dataset Splits | No | The paper mentions using MNIST and CIFAR-10 datasets, but it does not explicitly provide specific details on training, validation, or test dataset splits (e.g., percentages, sample counts, or direct citations to predefined splits used for reproduction). |
| Hardware Specification | Yes | We ran all experiments on the same Azure standard B8ms virtual machine with 8 v CPUs and 32GB DRAM. |
| Software Dependencies | Yes | We use BFV scheme in SEAL [21] to implement Falcon. [21] Microsoft SEAL (release 3.4). |
| Experiment Setup | Yes | For MNIST and CIFAR-10, the plaintext modulus t = 2148728833 2148794369 2149810177, modulus degree N = 16384, coefficient modulus Q = 440 bits. More specific encryption parameters settings are shown in Table 7 and Table 8. The block size k of circulant matrix is set as 8 so that accuracy is not decreased. To keep original accuracy, the block size k = 16 of circulant matrix is used. |