User Feedback to Improve the Performance of a Cyberattack Detection Artificial Intelligence System in the e-Health Domain - Human-Computer-Interaction – INTERACT 2021 Access content directly
Conference Papers Year : 2021

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

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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hal-04291205 , version 1 (17-11-2023)

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Carmelo Ardito, Tommaso Di Di Noia, Eugenio Di Sciascio, Domenico Lofù, Andrea Pazienza, et al.. User Feedback to Improve the Performance of a Cyberattack Detection Artificial Intelligence System in the e-Health Domain. 18th IFIP Conference on Human-Computer Interaction (INTERACT), Aug 2021, Bari, Italy. pp.295-299, ⟨10.1007/978-3-030-85607-6_25⟩. ⟨hal-04291205⟩
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