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http://dx.doi.org/10.9723/jksiis.2018.23.5.009

Deep Learning Based Fake Face Detection  

Kim, DaeHee (한밭대학교 제어계측공학과)
Choi, SeungWan (한밭대학교 제어계측공학과)
Kwak, SooYeong (한밭대학교 전자제어공학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.23, no.5, 2018 , pp. 9-17 More about this Journal
Abstract
Recently, the increasing interest of biometric systems has led to the creation of many researches of biometrics forgery. In order to solve this forgery problem, this paper proposes a method of determining whether a synthesized face made of artificaial intelligence is real face or fake face. The proposed algorithm consists of two steps. Firstly, we create the fake face images using various GAN (Generative Adversarial Networks) algorithms. After that, deep learning algorithm can classify the real face image and the generated face image. The experimental results shows that the proposed algorithm can detect the fake face image which looks like the real face. Also, we obtained the classification accuracy of 88.7%.
Keywords
Fake Face; GAN; Deep Learning;
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