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Privacy and DRM Requirements for Collaborative Development of AI Application
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Institute of technology. (Cloud, Networking and Security)ORCID iD: 0000-0002-0128-4127
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. (Cloud, Networking and Security)ORCID iD: 0000-0001-8453-447X
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. (Cloud, Networking and Security)ORCID iD: 0000-0003-4814-4428
2018 (English)In: ACM International Conference Proceeding Series, 2018, article id 3233268Conference paper, Published paper (Refereed)
Abstract [en]

The use of data is essential for the capabilities of Data-driven Artificial intelligence (AI), Deep Learning and Big Data analysis techniques. This data usage, however, raises intrinsically the concerns on data privacy. In addition, supporting collaborative development of AI applications across organisations has become a major need in AI system design. Digital Rights Management (DRM) is required to protect intellectual property in such collaboration. As a consequence of DRM, privacy threats and privacy-enforcing mechanisms will interact with each other.

This paper describes the privacy and DRM requirements in collaborative AI system design using AI pipelines. It describes the relationships between DRM and privacy and outlines the threats against these non-functional features. Finally, the paper provides first security architecture to protect against the threats on DRM and privacy in collaborative AI design using AI pipelines. 

Place, publisher, year, edition, pages
2018. article id 3233268
Keywords [en]
Privacy, DRM, AI, collaborative
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-16867DOI: 10.1145/3230833.3233268ISBN: 978-1-4503-6448-5 (print)OAI: oai:DiVA.org:bth-16867DiVA, id: diva2:1238658
Conference
13th International Conference on Availability, Reliability and Security, ARES 2018; Hamburg; Germany; 27 August 2018 through 30 August
Projects
H2020 Bonseyes
Funder
EU, Horizon 2020, 732204Available from: 2018-08-14 Created: 2018-08-14 Last updated: 2019-01-30Bibliographically approved

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Ahmadi Mehri, VidaIlie, DragosTutschku, Kurt
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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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