Skip to main content
Book cover

Computational Intelligence in Security for Information Systems Conference

CISIS 2019: 13th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2020) pp 208–217Cite as

Distributed Architecture for Fake News Detection

  • 644 Accesses

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

Abstract

Countering the fake news phenomenon has become one of the most important challenges for democratic societies, governments and non-profit organizations, as well as for the researchers coming from several domains. This is not a local problem, and demands a holistic approach to analyzing heterogeneous data and storing the results. The major contribution of this paper is the proposition of an innovative distributed architecture to tackle the above-mentioned problems. The architecture uses state-of-the-art technologies with focus on efficiency, scalability and also openness, so that community-created components and analyzers could be added.

Keywords

  • Fake news detection
  • Distributed architecture
  • Machine learning
  • Deep learning

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-57805-3_20
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   149.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-57805-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   199.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

References

  1. FakeBox project homepage. https://machinebox.io/docs/fakebox. Accessed 09 Feb 2020

  2. Fighthoax project website. http://fighthoax.com. Accessed 09 Feb 2020

  3. Truly Media tackles fake news ahead of German elections. https://www.truly.media/truly-media-tackles-fake-news-ahead-of-german-elections/ Accessed 09 Feb 2020

  4. Ahmed, H., Traore, I., Saad, S.: Detecting opinion spams and fake news using text classification. Secur. Privacy 1(1), e9 (2018)

    CrossRef  Google Scholar 

  5. Akbik, A., Blythe, D., Vollgraf, R.: Contextual string embeddings for sequence labeling. In: COLING 2018, 27th International Conference on Computational Linguistics, pp. 1638–1649 (2018)

    Google Scholar 

  6. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)

    CrossRef  Google Scholar 

  7. Choras, M., Gielczyk, A., Demestichas, K.P., Puchalski, D., Kozik, R.: Pattern recognition solutions for fake news detection. In: Saeed, K., Homenda, W. (eds.) Computer Information Systems and Industrial Management - 17th International Conference, CISIM 2018, Olomouc, Czech Republic, 27–29 September 2018, Proceedings, Lecture Notes in Computer Science, vol. 11127, pp. 130–139. Springer (2018)

    Google Scholar 

  8. Choras, M., Pawlicki, M., Kozik, R., Demestichas, K.P., Kosmides, P., Gupta, M.: Socialtruth project approach to online disinformation (fake news) detection and mitigation. In: Proceedings of the 14th International Conference on Availability, Reliability and Security, ARES 2019, Canterbury, UK, 26–29 August 2019, pp. 68:1–68:10. ACM (2019)

    Google Scholar 

  9. de Graaf, K.A., Khalili, A.: Slidewiki microservice architecture for collaborative online system development. In: 10th ACM Conference on Web Science, WebSci 2018. ACM, March 2018

    Google Scholar 

  10. Domm, P.: False Rumor of explosion at white house causes stocks to briefly plunge; AP Confirms Its Twitter Feed Was Hacked. https://www.cnbc.com/id/100646197

  11. Farand, C.: French social media awash with fake news stories from sources ’exposed to Russian influence’ ahead of presidential election. https://tinyurl.com/y5gdzvz4

  12. Goodman, M.: The sun and the moon: the remarkable true account of hoaxers, showmen. Dueling Journalists, and Lunar Man-Bats in Nineteenth-Century New York (2008)

    Google Scholar 

  13. Ahmed, H., Traoré, I., Saad, S.: Detection of online fake news using n-gram analysis and machine learning techniques. In: Traoré, I., Woungang, I., and Awad, A. (eds.) ISDDC, pp. 127–138 (2017)

    Google Scholar 

  14. Ahmed, H., Traoré, I., Saad, S.: Detecting opinion spams and fake news using text classification. J. Secur. Privacy (2018)

    Google Scholar 

  15. MATHEW INGRAM. Google’s Fake News Problem Could Be Worse Than on Facebook. http://fortune.com/2017/03/06/google-facebook-fake-news/

  16. Lawler, J.P., Hortense Howell-Barber. Service-Oriented Architecture: SOA Strategy, Methodology, and Technology. Auerbach Publications (2007)

    Google Scholar 

  17. Naik, N.: Building a virtual system of systems using docker swarm in multiple clouds. In: 2016 IEEE International Symposium on Systems Engineering (ISSE), pp. 1–3. IEEE (2016)

    Google Scholar 

  18. Pautasso, C., Zimmermann, O., Amundsen, M., Lewis, J., Josuttis, N.: Microservices in practice, Part 1: reality check and service design. IEEE Software 1, 91–98 (2017)

    CrossRef  Google Scholar 

  19. Peltz, C.: Web services orchestration and choreography. Computer 36(10), 46–52 (2003)

    CrossRef  Google Scholar 

  20. Ren, M., Lyytinen, K.J.: Building enterprise architecture agility and sustenance with SOA. Commun. Assoc. Inf. Syst. 22(1), 4 (2008)

    Google Scholar 

Download references

Acknowledgement

This work is funded under SocialTruth project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 825477.

Author information

Authors and Affiliations

  1. UTP University of Science and Technology, Kaliskiego 7, 85-976, Bydgoszcz, Poland

    Rafał Kozik, Michał Choraś, Sebastian Kula & Marek Pawlicki

  2. Kazimierz Wielki University, UKW Bydgoszcz, Bydgoszcz, Poland

    Sebastian Kula

Authors
  1. Rafał Kozik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michał Choraś
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sebastian Kula
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marek Pawlicki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rafał Kozik .

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

    Dr. Daniel Urda

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

    Prof. Dr. Javier Sedano

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

    Héctor Quintián

  6. University of Salamanca, Salamanca, Spain

    Emilio Corchado

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Kozik, R., Choraś, M., Kula, S., Pawlicki, M. (2021). Distributed Architecture for Fake News Detection. 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_20

Download citation