mlsanityData to 7 Oct 2026

An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications

arXiv 2201.11006 ↗First posted 26 Jan 2022cs.CV cs.CRcited by 29

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Abstract (arXiv)

This article presents an overview of image transformation with a secret key and its applications. Image transformation with a secret key enables us not only to protect visual information on plain images but also to embed unique features controlled with a key into images. In addition, numerous encryption methods can generate encrypted images that are compressible and learnable for machine learning. Various applications of such transformation have been developed by using these properties. In this paper, we focus on a class of image transformation referred to as learnable image encryption, which is applicable to privacy-preserving machine learning and adversarially robust defense. Detailed descriptions of both transformation algorithms and performances are provided. Moreover, we discuss robustness against various attacks.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 36 of its 103 references that are in the map. First posted on arXiv 26 Jan 2022.

Builds on

36 of 103 references.

References · 36

  1. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  2. 2013Intriguing properties of neural networkscited by 5,114
  3. 2016Towards Evaluating the Robustness of Neural Networkscited by 2,976
  4. 2016Membership Inference Attacks against Machine Learning Modelscited by 2,221
  5. 2015Deep Learning and the Information Bottleneck Principlecited by 793
  6. 2020Fast is better than free: Revisiting adversarial trainingcited by 723
  7. 2017Evasion Attacks against Machine Learning at Test Timecited by 686
  8. 2018Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooringcited by 334
  9. 2017Embedding Watermarks into Deep Neural Networkscited by 227
  10. 2017EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examplescited by 154
  11. 2020Adversarial Machine Learning -- Industry Perspectivescited by 121
  12. 2017Adversarial Frontier Stitching for Remote Neural Network Watermarkingcited by 110
24 more
  1. 2019Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Trainingcited by 95
  2. 2018Learnable Image Encryptioncited by 33
  3. 2018Encryption-then-Compression Systems using Grayscale-based Image Encryption for JPEG Imagescited by 33
  4. 2020Block-wise Image Transformation with Secret Key for Adversarially Robust Defensecited by 30
  5. 2020Block-wise Scrambled Image Recognition Using Adaptation Networkcited by 27
  6. 2020A GAN-Based Image Transformation Scheme for Privacy-Preserving Deep Neural Networkscited by 27
  7. 2020Encryption Inspired Adversarial Defense for Visual Classificationcited by 17
  8. 2018DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Modelscited by 16
  9. 2021A Protection Method of Trained CNN Model with Secret Key from Unauthorized Accesscited by 15
  10. 2020Attacks on Image Encryption Schemes for Privacy-Preserving Deep Neural Networkscited by 12
  11. 2018Privacy-Preserving Deep Learning via Weight Transmissioncited by 10
  12. 2020A Privacy-Preserving Machine Learning Scheme Using EtC Imagescited by 9
  13. 2021Piracy-Resistant DNN Watermarking by Block-Wise Image Transformation with Secret Keycited by 9
  14. 2013P3: Toward Privacy-Preserving Photo Sharingcited by 8
  15. 2020Image Transformation Network for Privacy-Preserving Deep Neural Networks and Its Security Evaluationcited by 8
  16. 2018Bridging machine learning and cryptography in defence against adversarial attackscited by 5
  17. 2019Privacy-Preserving Support Vector Machine Computing Using Random Unitary Transformationcited by 5
  18. 2018Image Manipulation Specifications on Social Networking Services for Encryption-then-Compression Systemscited by 4
  19. 2021A Protection Method of Trained CNN Model Using Feature Maps Transformed With Secret Key From Unauthorized Accesscited by 4
  20. 2021Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Modelscited by 4
  21. 2020Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional Groupscited by 3
  22. 2020A Reversible Data Hiding Method in Compressible Encrypted Imagescited by 2
  23. 2016Cryptanalyzing an Image-Scrambling Encryption Algorithm of Pixel Bitscited by 1
  24. 2017An Automatic Solver for Very Large Jigsaw Puzzles Using Genetic Algorithmscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 13; 2023: 8; 2024: 6; 2025: 1; 2026: 1.

29 papers.

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  1. 2022Privacy-Preserving Image Classification Using Isotropic Networkcited by 17
  2. 2022Image and Model Transformation with Secret Key for Vision Transformercited by 12
  3. 2022Privacy-Preserving Image Classification Using Vision Transformercited by 9
  4. 2022On the Transferability of Adversarial Examples between Encrypted Modelscited by 4
  5. 2023Generative Model-Based Attack on Learnable Image Encryption for Privacy-Preserving Deep Learningcited by 4
  6. 2023Enhanced Security against Adversarial Examples Using a Random Ensemble of Encrypted Vision Transformer Modelscited by 4
  7. 2022Access Control of Semantic Segmentation Models Using Encrypted Feature Mapscited by 3
  8. 2024Efficient Fine-Tuning with Domain Adaptation for Privacy-Preserving Vision Transformercited by 3
  9. 2024A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defensecited by 3
  10. 2023Color-NeuraCrypt: Privacy-Preserving Color-Image Classification Using Extended Random Neural Networkscited by 2
  11. 2023Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddingscited by 2
  12. 2022Access Control of Object Detection Models Using Encrypted Feature Mapscited by 1
17 more
  1. 2022StyleGAN Encoder-Based Attack for Block Scrambled Face Imagescited by 1
  2. 2022Access Control with Encrypted Feature Maps for Object Detection Modelscited by 1
  3. 2023Domain Adaptation for Efficiently Fine-tuning Vision Transformer with Encrypted Imagescited by 1
  4. 2023Efficient Key-Based Adversarial Defense for ImageNet by Using Pre-trained Modelcited by 1
  5. 2024Privacy-Preserving Deep Learning Using Deformable Operators for Secure Task Learningcited by 1
  6. 2025A Privacy-Preserving Semantic-Segmentation Method Using Domain-Adaptation Techniquecited by 1
  7. 2022Adversarial Detector with Robust Classifiercited by 0
  8. 2022An Encryption Method of ConvMixer Models without Performance Degradationcited by 0
  9. 2022Privacy-Preserving Image Classification Using ConvMixer with Adaptive Permutation Matrixcited by 0
  10. 2022An Access Control Method with Secret Key for Semantic Segmentation Modelscited by 0
  11. 2022On the Adversarial Transferability of ConvMixer Modelscited by 0
  12. 2023A Privacy Preserving Method with a Random Orthogonal Matrix for ConvMixer Modelscited by 0
  13. 2023Combined Use of Federated Learning and Image Encryption for Privacy-Preserving Image Classification with Vision Transformercited by 0
  14. 2024A Random Ensemble of Encrypted models for Enhancing Robustness against Adversarial Examplescited by 0
  15. 2024Attack GAN (AGAN ): A new Security Evaluation Tool for Perceptual Encryptioncited by 0
  16. 2024Privacy-Preserving Vision Transformer Using Images Encrypted with Restricted Random Permutation Matricescited by 0
  17. 2026Privacy-Preserving Object Detection for Vision Transformer-Based Modelscited by 0