3 papers
cs.LG2025
Rethinking the Vulnerability of Concept Erasure and a New Method
Alex D. Richardson, Kaicheng Zhang, Lucas Beerens +1
The proliferation of text-to-image diffusion models has raised significant privacy and security concerns, particularly regarding the generation of copyrighted or harmful images. In…
cs.LG2025
Embedding Hidden Adversarial Capabilities in Pre-Trained Diffusion Models
Lucas Beerens, Desmond J. Higham
We introduce a new attack paradigm that embeds hidden adversarial capabilities directly into diffusion models via fine-tuning, without altering their observable behavior or requiri…
cs.LG2024
Deceptive Diffusion: Generating Synthetic Adversarial Examples
Lucas Beerens, Catherine F. Higham, Desmond J. Higham
We introduce the concept of deceptive diffusion -- training a generative AI model to produce adversarial images. Whereas a traditional adversarial attack algorithm aims to perturb…