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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2022: Artificial Intelligence and Soft Computing pp 277–285Cite as

Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13589))

Abstract

We present a new approach to anonymizing personal data in text files. In the conducted research, an approach was applied that enables the analysis of sentence sentences with the use of neural networks. Contrary to other currently proposed methods, the presented work analyzes the context of a fragment of the text, which enables the detection of sensitive information not only on the basis of specific words but on the basis of “understanding” the context, such as “mayor of Paris”, “son of the CEO” of a specific company. We present a proprietary solution using convolutional networks connected with glial cells, enabling the selection of the optimal size of the CNN network structure.

The work was supported by The National Centre for Research and Development (NCBR), the project no POIR.01.01.01-00-1431/19.

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Author information

Authors and Affiliations

  1. Czestochowa University of Technology, al. Armii Krajowej 36, Czestochowa, Poland

    Marcin Korytkowski, Jakub Nowak & Rafał Scherer

  2. Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, 710048, China

    Wei Wei

Authors
  1. Marcin Korytkowski
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  2. Jakub Nowak
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  3. Rafał Scherer
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  4. Wei Wei
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Corresponding author

Correspondence to Rafał Scherer .

Editor information

Editors and Affiliations

  1. Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Korytkowski, M., Nowak, J., Scherer, R., Wei, W. (2023). Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2022. Lecture Notes in Computer Science(), vol 13589. Springer, Cham. https://doi.org/10.1007/978-3-031-23480-4_23

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  • DOI: https://doi.org/10.1007/978-3-031-23480-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23479-8

  • Online ISBN: 978-3-031-23480-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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