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Conference Papers Year : 2017

Privacy and Trust in Cloud-Based Marketplaces for AI and Data Resources

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Abstract

The processing of the huge amounts of information from the Internet of Things (IoT) has become challenging. Artificial Intelligence (AI) techniques have been developed to handle this task efficiently. However, they require annotated data sets for training, while manual preprocessing of the data sets is costly. The H2020 project “Bonseyes” has suggested a “Market Place for AI”, where the stakeholders can engage trustfully in business around AI resources and data sets. The MP permits trading of resources that have high privacy requirements (e.g. data sets containing patient medical information) as well as ones with low requirements (e.g. fuel consumption of cars) for the sake of its generality. In this abstract we review trust and privacy definitions and provide a first requirement analysis for them with regards to Cloud-based Market Places (CMPs). The comparison of definitions and requirements allows for the identification of the research gap that will be addressed by the main authors PhD project.
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Dates and versions

hal-01651185 , version 1 (28-11-2017)

Licence

Attribution - CC BY 4.0

Identifiers

  • HAL Id : hal-01651185 , version 1

Cite

Vida Ahmadi, Kurt Tutschku. Privacy and Trust in Cloud-Based Marketplaces for AI and Data Resources. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. pp.223-225. ⟨hal-01651185⟩
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