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IFIP Conference on Human-Computer Interaction

INTERACT 2021: Human-Computer Interaction – INTERACT 2021 pp 295–299Cite as

User Feedback to Improve the Performance of a Cyberattack Detection Artificial Intelligence System in the e-Health Domain

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12936))

Abstract

New and evolving threats emerge every day in the e-Health industry. The safety of e-Health’s telemonitoring systems is becoming a prominent task. In this work, starting from a CADS (Cyberattack Detection System) model that uses artificial intelligence techniques to detect anomalies, we focus on the activity of interacting with data. Using a User Interaction Engine, a dashboard allows you to visually explore and view data from suspected attacks on healthcare professionals for a threat reaction. In particular, a User Feedback module is presented to interact with healthcare personnel and ask for a response on the anomaly detected.

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Acknowledgments

This work was partially funded by the European Union, Horizon 2020 research and innovation programme, through the ECHO project (grant agreement no 830943) and by the Italian P.O. Puglia FESR 2014–2020 (project code 6ESURE5) SECURE SAFE APULIA.

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Authors and Affiliations

  1. Politecnico di Bari, Via E. Orabona 4, 70125, Bari, Italy

    Carmelo Ardito, Tommaso Di Noia, Eugenio Di Sciascio & Domenico Lofù

  2. Innovation Lab, Exprivia S.p.A., Via A. Olivetti 11, 70056, Molfetta, Italy

    Domenico Lofù, Andrea Pazienza & Felice Vitulano

Authors
  1. Carmelo Ardito
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  2. Tommaso Di Noia
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  3. Eugenio Di Sciascio
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  4. Domenico Lofù
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  5. Andrea Pazienza
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  6. Felice Vitulano
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Corresponding author

Correspondence to Domenico Lofù .

Editor information

Editors and Affiliations

  1. Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy

    Carmelo Ardito

  2. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Rosa Lanzilotti

  3. Computer Science Department, University of Pisa, Pisa, Italy

    Alessio Malizia

  4. Department of Computer Science, University of York, York, UK

    Helen Petrie

  5. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Antonio Piccinno

  6. Computer Science Department, University of Bari Aldo Moro, Bari, Italy

    Giuseppe Desolda

  7. Microsoft Research, Redmond, WA, USA

    Kori Inkpen

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Ardito, C., Di Noia, T., Di Sciascio, E., Lofù, D., Pazienza, A., Vitulano, F. (2021). User Feedback to Improve the Performance of a Cyberattack Detection Artificial Intelligence System in the e-Health Domain. In: Ardito, C., et al. Human-Computer Interaction – INTERACT 2021. INTERACT 2021. Lecture Notes in Computer Science(), vol 12936. Springer, Cham. https://doi.org/10.1007/978-3-030-85607-6_25

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  • DOI: https://doi.org/10.1007/978-3-030-85607-6_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85606-9

  • Online ISBN: 978-3-030-85607-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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