Manipulate to Obfuscate: A Privacy-Focused Intelligent Image Manipulation Tool for End-Users

Image-related privacy preservation techniques often demand significant technical expertise, creating a barrier for end-users. We present a privacy-focused intelligent image manipulation tool that leverages recent advancements in generative AI to lower this barrier. Our functional prototype allows users to express their privacy concerns, identify potential privacy risks in images, and recommends relevant AI-powered obfuscation techniques to mitigate these risks and concerns. We demonstrate the tool’s versatility across multiple different domains, showcasing its potential to empower users in managing their privacy across various contexts. This demonstration presents the concept, user workflow, and implementation details of our prototype, highlighting its potential to bridge the gap between privacy research and practical, user-facing tools for privacy-preserving image sharing.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3672539.3686778
Citations
3
Primary Topic
Advanced Steganography and Watermarking Techniques
Type
article
Field-Weighted Citation Impact
0.75
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article

Manipulate to Obfuscate: A Privacy-Focused Intelligent Image Manipulation Tool for End-Users

Sauvik Das, Kyzyl Monteiro, Yuchen Wu
3 citations
Advanced Steganography and Watermarking Techniques
0.75
article

Manipulate to Obfuscate: A Privacy-Focused Intelligent Image Manipulation Tool for End-Users

Sauvik Das, Kyzyl Monteiro, Yuchen Wu
article en
3 citations

Abstract

Image-related privacy preservation techniques often demand significant technical expertise, creating a barrier for end-users. We present a privacy-focused intelligent image manipulation tool that leverages recent advancements in generative AI to lower this barrier. Our functional prototype allows users to express their privacy concerns, identify potential privacy risks in images, and recommends relevant AI-powered obfuscation techniques to mitigate these risks and concerns. We demonstrate the tool’s versatility across multiple different domains, showcasing its potential to empower users in managing their privacy across various contexts. This demonstration presents the concept, user workflow, and implementation details of our prototype, highlighting its potential to bridge the gap between privacy research and practical, user-facing tools for privacy-preserving image sharing.

Carnegie Mellon University (US), Tsinghua University (CN)
Reduced inequalities
Openalex Percentile: Top 27%
Advanced Steganography and Watermarking Techniques
0.75
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Manipulate to Obfuscate: A Privacy-Focused Intelligent Image Manipulation Tool for End-Users — Sauvik Das, Kyzyl Monteiro, et al. · (2024) | TGRS Research Map | TGRS