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Towards a Privacy Compliant Cloud Architecture for Natural Language Processing Platforms

: Blohm, Matthias; Dukino, Claudia; Kintz, Maximilien; Kochanowski, Monika; Kötter, Falko; Renner, Thomas


Filipe, Joaquim (Ed.) ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
21st International Conference on Enterprise Information Systems, ICEIS 2019. Proceedings. Vol.1 : May 3-5, 2019, in Heraklion, Crete, Greece
SciTePress, 2019
ISBN: 978-989-758-372-8
International Conference on Enterprise Information Systems (ICEIS) <21, 2019, Heraklion>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Innovationen für die Produktion, Dienstleistung und Arbeit von morgen; 02L17B00ff; SmartAIwork
Zukunft der Betriebsabläufe: Sachbearbeitung zukunftsorientiert gestalten mit Automatisierung durch Künstliche Intelligenz
Conference Paper
Fraunhofer IAO ()

Natural language processing in combination with advances in artificial intelligence is on the rise. However, compliance constraints while handling personal data in many types of documents hinder various application scenarios. We describe the challenges of working with personal and particularly sensitive data in practice with three different use cases. We present the anonymization bootstrap challenge in creating a prototype in a cloud environment. Finally, we outline an architecture for privacy compliant AI cloud applications and an anonymization tool. With these preliminary results, we describe future work in bridging privacy and AI.