Tiffany Souterre

Tiffany Souterre

Tiffany Souterre

About Tiffany

I love science and I love data! After finishing a PhD in genetic engineering, I continued my quest for discovering new patterns through data science and machine learning. I currently work as a Data Engineer and I play with machine learning algorithms on my free time. Someday, I wish to leverage artificial intelligence and genetics to improve people's life.

Benford’s law to detect GAN-generated images

Generative Adversarial Network (GAN) generated images are synthetic images generated by artificial intelligence. These images can be so realistic that they can fool humans into thinking that what they are seeing is real. Malicious use of this technology may seriously impact our society through fake news for example. Being able to detect whether an image is fake or real might be one of the greatest challenges against disinformation. During this talk, we will discover the strange property of Benford’s law and how it can help us discriminate against a GAN-generated image from a natural one.


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