P3: Toward Privacy-Preserving Photo Sharing
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Abstract (arXiv)
With increasing use of mobile devices, photo sharing services are experiencing greater popularity. Aside from providing storage, photo sharing services enable bandwidth-efficient downloads to mobile devices by performing server-side image transformations (resizing, cropping). On the flip side, photo sharing services have raised privacy concerns such as leakage of photos to unauthorized viewers and the use of algorithmic recognition technologies by providers. To address these concerns, we propose a privacy-preserving photo encoding algorithm that extracts and encrypts a small, but significant, component of the photo, while preserving the remainder in a public, standards-compatible, part. These two components can be separately stored. This technique significantly reduces the signal-to-noise ratio and the accuracy of automated detection and recognition on the public part, while preserving the ability of the provider to perform server-side transformations to conserve download bandwidth usage. Our prototype privacy-preserving photo sharing system, P3, works with Facebook, and can be extended to other services as well. P3 requires no changes to existing services or mobile application software, and adds minimal photo storage overhead.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Feb 2013.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 0; 2024: 0; 2025: 3; 2026: 1.
8 papers.
- 2022An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applicationscited by 29
- 2022Image and Model Transformation with Secret Key for Vision Transformercited by 12
- 2021Multitask Identity-Aware Image Steganography via Minimax Optimizationcited by 2
- 2025Semantics versus Identity: A Divide-and-Conquer Approach towards Adjustable Medical Image De-Identificationcited by 2
- 2021A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learningcited by 0
- 2025On the Importance of Conditioning for Privacy-Preserving Data Augmentationcited by 0
- 2025Pruning Overparameterized Multi-Task Networks for Degraded Web Image Restorationcited by 0
- 2026AuraMask: An Extensible Pipeline for Developing Aesthetic Anti-Facial Recognition Image Filterscited by 0
- 2026AuraMask: An Extensible Pipeline for Developing Aesthetic Anti-Facial Recognition Image Filters13 May 2026
- 2025Pruning Overparameterized Multi-Task Networks for Degraded Web Image Restoration16 Oct 2025
- 2025Semantics versus Identity: A Divide-and-Conquer Approach towards Adjustable Medical Image De-Identification25 Jul 2025
- 2025On the Importance of Conditioning for Privacy-Preserving Data Augmentation8 Apr 2025
- 2022Image and Model Transformation with Secret Key for Vision Transformer12 Jul 2022
- 2022An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applications26 Jan 2022
- 2021Multitask Identity-Aware Image Steganography via Minimax Optimization13 Jul 2021
- 2021A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning19 May 2021