Acknowledgement
Following are results of a study on the "Convergence and Open Sharing System" Project, supported by the Ministry of Education and National Research Foundation of Korea.
References
- Sowoon Kim, Sungtaek Lee, "Development of Voice Phishing Damage Prevention Service Misusing Deep," The Journal of Korean Institute of Communications and Information Sciences, Vol. 47, No. 10, pp. 1677-1685, Oct 2022. https://doi.org/10.7840/kics.2022.47.10.1677
- Anupama Chadha, Vaibhav Kumar, Sonu Kashyap, Mayank Gupta, "Deepfake: An Overview," Proceedings of Second International Conference on Computing, Communications, and Cyber-Security, Vol. 203, pp. 557-566, May 2021.
- Seung-Woo Han, Seong-Hun Han, Seong-Min You, Dong-Ho Song, Chang-Jin Seo, "A Study on the Development of Deep Learning-Based Deep Voice Detection System Using Mel-Spectrogram and MFCC," The Transaction of The Korean Institute of Electrical Engineers, Vol. 72P, No. 3, pp. 186-192, Sept 2023.
- Dae-hyeon Lee, Jong-sub Moon, "A Method of Detection of Deepfake Using Bidirectional Convolutional LSTM," Journal of The Korea Institute of Information Security and Cryptology, Vol. 30, No. 6, pp. 1053-1065, Dec 2020.
- Seok Bin Son, Hee Hyeon Jo, Hee Yoon Kang, Byung Gul Lee, Youn Kyu Lee, "A Comparative Study on Deepfake Detection using Gray Channel Analysis," Journal of Korea Multimedia Society, Vol. 24, No. 9, pp. 1224-1241, Sept 2021.