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has been cited by the following article:

• TITLE: Countermeasure against Deepfake Using Steganography and Facial Detection

  AUTHORS: Kyle Corcoran, Jacob Ressler, Ye Zhu

  KEYWORDS: Deepfake, Deepfake Detection, Steganography, Cryptography, Facial Detection

  JOURNAL NAME: Journal of Computer and Communications, Vol.9 No.9, September 30, 2021

  ABSTRACT: As deepfake technology continues to advance at a rapid pace, there is a constant need to develop new methods to counteract its use. Physical copies of authentic items like signed baseball memorabilia use a certification to identify the authenticity. This paper proposes using steganography to embed a signed watermark inside a digital image. By using RSA to generate, sign, and verify the watermark, individuals will be able to authenticate personal images or try to verify signed images for authenticity. We evaluate the proposed approach with images manipulated by deepfake algorithms. The experiment results show 100% detection rate on deepfake images. The signing time and the verification time are around 300 ms according to our experiments. So the overhead of the countermeasure are negligible.