Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption - Robotics Institute Carnegie Mellon University

Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption

Ryo Yonetani, Vishnu Naresh Boddeti, Kris M. Kitani, and Yoichi Sato
Conference Paper, Proceedings of (ICCV) International Conference on Computer Vision, pp. 2059 - 2069, October, 2017

Abstract

We propose a privacy-preserving framework for learning visual classifiers by leveraging distributed private image data. This framework is designed to aggregate multiple classifiers updated locally using private data and to ensure that no private information about the data is exposed during and after its learning procedure. We utilize a homomorphic cryptosystem that can aggregate the local classifiers while they are encrypted and thus kept secret. To overcome the high computational cost of homomorphic encryption of high-dimensional classifiers, we (1) impose sparsity constraints on local classifier updates and (2) propose a novel efficient encryption scheme named doublypermuted homomorphic encryption (DPHE) which is tailored to sparse high-dimensional data. DPHE (i) decomposes sparse data into its constituent non-zero values and their corresponding support indices, (ii) applies homomorphic encryption only to the non-zero values, and (iii) employs double permutations on the support indices to make them secret. Our experimental evaluation on several public datasets shows that the proposed approach achieves comparable performance against state-of-the-art visual recognition methods while preserving privacy and significantly outperforms other privacy-preserving methods.

BibTeX

@conference{Yonetani-2017-109792,
author = {Ryo Yonetani and Vishnu Naresh Boddeti and Kris M. Kitani and Yoichi Sato},
title = {Privacy-Preserving Visual Learning Using Doubly Permuted Homomorphic Encryption},
booktitle = {Proceedings of (ICCV) International Conference on Computer Vision},
year = {2017},
month = {October},
pages = {2059 - 2069},
}