| Title | A Measurement Study on Gray Channel-based Deepfake Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Son, Seok Bin, Park, Seong Hee, Lee, Youn Kyu |
| Conference Name | 2021 International Conference on Information and Communication Technology Convergence (ICTC) |
| Date Published | oct |
| Keywords | Analytical models, Brightness, Deep Learning, DeepFake, deepfake detection, gray-channel analysis, human factors, information and communication technology, Information integrity, Metrics, pubcrawl, resilience, Resiliency, Scalability, security, Videos |
| Abstract | Deepfake detection techniques have been widely studied to resolve security issues. However, existing techniques mainly focused on RGB channel-based analysis, which still shows incomplete detection accuracy. In this paper, we validate the performance of Gray channel-based deepfake detection. To compare RGB channel-based analysis and Gray channel-based analysis in deepfake detection, we quantitatively measured the performance by using popular CNN models, deepfake datasets, and evaluation indicators. Our experimental results confirm that Gray channel-based deepfake detection outperforms RGB channel-based deepfake detection in terms of accuracy and analysis time. |
| DOI | 10.1109/ICTC52510.2021.9621082 |
| Citation Key | son_measurement_2021 |
A Measurement Study on Gray Channel-based Deepfake Detection