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Detection of Artificial Images and Changes in Real Images Using Convolutional Neural Networks

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13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020) (CISIS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1267))

Abstract

Image recognition has now become one of the most popular methods used in the entertainment industry, media, automotive, etc. The possibilities provided by neural networks and deep learning algorithms, cause the development of various methods for generating, modifying and falsifying information. An example would be the use of deep learning algorithms to replace faces in a video recording. Social networks, video materials are full of fake video and images. Our work proposes a method of detecting forgery on real images and detecting artificially generated images using Convolutional Neural Networks (CNN). Our approach introduces the possibility of classifying images into one of three classes: the class of real images, the class of real and modified images, and the class of artificially generated images. An important element of our work is the practical detection of modified or artificially generated images that could be used when phishing biometrically protected data. The research has been narrowed down to the facial images of people of different skin colour, nationality and age. The conducted tests show the acceptable effectiveness of our method and become a positive element of further experiments.

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Acknowledgements

The project financed under the program of the Polish Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in the years 2019–2022 project number 020/RID/2018/19, the amount of financing 12,000,000 PLN.

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Authors and Affiliations

  1. Institute of Computer and Information Sciences, Czestochowa University of Technology, Dabrowskiego Street 69, 42-201, Czestochowa, Poland

    Mariusz Kubanek, Kamila Bartłomiejczyk & Janusz Bobulski

Authors
  1. Mariusz Kubanek
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  2. Kamila Bartłomiejczyk
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  3. Janusz Bobulski
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Corresponding author

Correspondence to Mariusz Kubanek .

Editor information

Editors and Affiliations

  1. Grupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain

    Álvaro Herrero

  2. Grupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain

    Carlos Cambra

  3. Grupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad de Burgos, Burgos, Spain

    Daniel Urda

  4. Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  5. Department of Industrial Engineering, University of A Coruña, La Coruña, Spain

    Héctor Quintián

  6. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Kubanek, M., Bartłomiejczyk, K., Bobulski, J. (2021). Detection of Artificial Images and Changes in Real Images Using Convolutional Neural Networks. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020). CISIS 2019. Advances in Intelligent Systems and Computing, vol 1267. Springer, Cham. https://doi.org/10.1007/978-3-030-57805-3_19

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