An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat Landscape

arXiv:2404.16212v1 Announce Type: new
Abstract: Deepfake or synthetic images produced using deep generative models pose serious risks to online platforms. This has triggered several research efforts to accurately detect deepfake images, achieving excellent performance on publicly available deepfake datasets. In this work, we study 8 state-of-the-art detectors and argue that they are far from being ready for deployment due to two recent developments. First, the emergence of lightweight methods to customize large generative models, can enable an attacker to create …

analysis art arxiv cs.cr cs.cv cs.lg datasets deepfake deepfake images detect detection generative generative models image images online platforms performance platforms research risks serious state study synthetic threat threat landscape work