# A Jigsaw Puzzle Solver-based Attack on Block-wise Image Encryption for Privacy-preserving DNNs

arXiv: https://arxiv.org/abs/2211.02369 · HTML: https://mlsanity.com/paper/2211.02369/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Nov 2022.

## Built on by (most cited first, 2 of 2)

- [Privacy-Preserving Remote Heart Rate Estimation from Facial Videos](https://mlsanity.com/paper/2306.01141/) (2023)
- [Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding](https://mlsanity.com/paper/2408.04261/) (2024)

## Abstract (arXiv)

Privacy-preserving deep neural networks (DNNs) have been proposed for protecting data privacy in the cloud server. Although several encryption schemes for visually protection have been proposed for privacy-preserving DNNs, several attacks enable to restore visual information from encrypted images. On the other hand, it has been confirmed that the block-wise image encryption scheme which utilizes block and pixel shuffling is robust against several attacks. In this paper, we propose a jigsaw puzzle solver-based attack to restore visual information from encrypted images including block and pixel shuffling. In experiments, images encrypted by using the block-wise image encryption are mostly restored by using the proposed attack.