Privacy and trust in cloud-based marketplaces for AI and data resources

• 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. © IFIP International Federation for Information Processing 2017.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)

Nyckelord

AI

Cloud

IoT

Marketplace

Privacy

Trust

Artificial intelligence

Clouds

Commerce

Internet of things

Trusted computing

Data resources

Internet of thing (IOT)

Medical information

Privacy and trusts

Privacy requirements

Requirement analysis

Data privacy

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