Research on Self-Evolving Deepfake Detection Technology Based on LLM
Deepfake technology enables the manipulation of text, images, audio, and video, offering innovative applications in areas like virtual reality and entertainment. However, it also poses risks such as fake news, privacy breaches, and political misuse, challenging existing static detection models that struggle to adapt to evolving manipulation techniques. This study proposes a self-evolving deepfake detection system using generative AI (LLM) to learn and adapt in real time. The framework integrates real-time learning, multimodal data processing, and lightweight models, emphasizing ethical data practices to ensure fairness, transparency, and security. By addressing technical, social, and legal challenges, this research provides a robust solution for mitigating deepfake risks while fostering ethical and reliable AI deployment.
Authors
- Cheolhee Yoon (ORCID: https://orcid.org/0000-0002-4862-4790)
- Junghyun Cho (ORCID: https://orcid.org/0000-0003-1913-8037)
- Kang Jang Mook
Institutions
- Korean National Police University (KR)
- Far East University (KR)
Publication Details
- Published
- 2025-03-29
- DOI
- https://doi.org/10.1109/icct-pacific63901.2025.11012805
- Primary Topic
- Anomaly Detection Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00