Deepfake Sentry: Harnessing Ensemble Intelligence for Resilient Detection and Generalisation

arXiv:2404.00114v1 Announce Type: new
Abstract: Recent advancements in Generative Adversarial Networks (GANs) have enabled photorealistic image generation with high quality. However, the malicious use of such generated media has raised concerns regarding visual misinformation. Although deepfake detection research has demonstrated high accuracy, it is vulnerable to advances in generation techniques and adversarial iterations on detection countermeasures. To address this, we propose a proactive and sustainable deepfake training augmentation solution that introduces artificial fingerprints into models. We achieve this by employing …

abstract accuracy advances adversarial arxiv concerns cs.cv deepfake detection ensemble gans generated generative generative adversarial networks however image image generation intelligence media misinformation networks photorealistic quality research resilient sentry type visual vulnerable