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The growing accessibility of diffusion models has revolutionized image editing but also raised significant concerns about unauthorized modifications, such as misinformation and plagiarism. Existing countermeasures largely rely on…

Computer Vision and Pattern Recognition · Computer Science 2025-03-07 Yaopei Zeng , Yuanpu Cao , Lu Lin

The remarkable image generation capabilities of state-of-the-art diffusion models, such as Stable Diffusion, can also be misused to spread misinformation and plagiarize copyrighted materials. To mitigate the potential risks associated with…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Qiuyu Tang , Bonor Ayambem , Mooi Choo Chuah , Aparna Bharati

Recent advances in text-to-image models have increased the exposure of powerful image editing techniques as a tool, raising concerns about their potential for malicious use. An emerging line of research to address such threats focuses on…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Jinsu Kim , Yunhun Nam , Minseon Kim , Sangpil Kim , Jongheon Jeong

With advances in diffusion models, image generation has shown significant performance improvements. This raises concerns about the potential abuse of image generation, such as the creation of explicit or violent images, commonly referred to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Junha Park , Jaehui Hwang , Ian Ryu , Hyungkeun Park , Jiyoon Kim , Jong-Seok Lee

Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturbing imagery when provided with harmful inputs. Existing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

Diffusion-based text-to-image models have shown immense potential for various image-related tasks. However, despite their prominence and popularity, customizing these models using unauthorized data also brings serious privacy and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Sen Peng , Jijia Yang , Mingyue Wang , Jianfei He , Xiaohua Jia

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Recently developed text-to-image diffusion models make it easy to edit or create high-quality images. Their ease of use has raised concerns about the potential for malicious editing or deepfake creation. Imperceptible perturbations have…

Machine Learning · Computer Science 2023-04-11 Pedro Sandoval-Segura , Jonas Geiping , Tom Goldstein

Diffusion models build a new milestone for image generation yet raising public concerns, for they can be fine-tuned on unauthorized images for customization. Protection based on adversarial attacks rises to encounter this unauthorized…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Boyang Zheng , Chumeng Liang , Xiaoyu Wu

Recent advances in diffusion models have introduced a new era of text-guided image manipulation, enabling users to create realistic edited images with simple textual prompts. However, there is significant concern about the potential misuse…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 June Suk Choi , Kyungmin Lee , Jongheon Jeong , Saining Xie , Jinwoo Shin , Kimin Lee

With the advancement of personalized image generation technologies, concerns about forgery attacks that infringe on portrait rights and privacy are growing. To address these concerns, protection perturbation algorithms have been developed…

Cryptography and Security · Computer Science 2025-08-11 Zelin Li , Ruohan Zong , Yifan Liu , Ruichen Yao , Yaokun Liu , Yang Zhang , Dong Wang

Advancements in diffusion models have enabled effortless image editing via text prompts, raising concerns about image security. Attackers with access to user images can exploit these tools for malicious edits. Recent defenses attempt to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-04 Aniruddha Bala , Rohit Chowdhury , Rohan Jaiswal , Siddharth Roheda

Recent advancements in diffusion models have made generative image editing more accessible, enabling creative edits but raising ethical concerns, particularly regarding malicious edits to human portraits that threaten privacy and identity…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Hanhui Wang , Yihua Zhang , Ruizheng Bai , Yue Zhao , Sijia Liu , Zhengzhong Tu

Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized modifications. To address this, we propose SecureT2I, a…

Cryptography and Security · Computer Science 2025-07-08 Xiaodong Wu , Xiangman Li , Qi Li , Jianbing Ni , Rongxing Lu

Face manipulation methods can be misused to affect an individual's privacy or to spread disinformation. To this end, we introduce a novel data-driven approach that produces image-specific perturbations which are embedded in the original…

Computer Vision and Pattern Recognition · Computer Science 2022-07-27 Shivangi Aneja , Lev Markhasin , Matthias Niessner

Text-to-image diffusion models are nothing but a revolution, allowing anyone, even without design skills, to create realistic images from simple text inputs. With powerful personalization tools like DreamBooth, they can generate images of a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Thanh Van Le , Hao Phung , Thuan Hoang Nguyen , Quan Dao , Ngoc Tran , Anh Tran

State-of-the-art Diffusion Models (DMs) produce highly realistic images. While prior work has successfully mitigated Not Safe For Work (NSFW) content in the visual domain, we identify a novel threat: the generation of NSFW text embedded…

Computer Vision and Pattern Recognition · Computer Science 2026-01-16 Aditya Kumar , Tom Blanchard , Adam Dziedzic , Franziska Boenisch

Online media data, in the forms of images and videos, are becoming mainstream communication channels. However, recent advances in deep learning, particularly deep generative models, open the doors for producing perceptually convincing…

Computer Vision and Pattern Recognition · Computer Science 2022-12-13 Junke Wang , Zhenxin Li , Chao Zhang , Jingjing Chen , Zuxuan Wu , Larry S. Davis , Yu-Gang Jiang

Diffusion models like Stable Diffusion have become prominent in visual synthesis tasks due to their powerful customization capabilities, which also introduce significant security risks, including deepfakes and copyright infringement. In…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Wenkui Yang , Jie Cao , Junxian Duan , Ran He

In the past years, we have witnessed the remarkable success of Text-to-Image (T2I) models and their widespread use on the web. Extensive research in making T2I models produce hyper-realistic images has led to new concerns, such as…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Muhammad Shahid Muneer , Simon S. Woo
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