Abstract
This paper describes an agent-based, incentive-driven, and privacy-preserving information sharing framework. Main contribution of the paper is to give the data provider agent an active role in the information sharing process and to change the currently asymmetric position between the provider and the requester of data and information (DI) to the favor of the DI provider. Instead of a binary yes/no answer to the requester’s data request and the incentive offer, the provider may negotiate about excluding from the requested DI bundle certain pieces of DI with high privacy value, and/or ask for a different type of incentive. We show the presented approach on a use case. However, the proposed architecture is domain independent.
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Notes
- 1.
From now on we use DI to refer to “data and information” but also interchangeably use only “data” or only “information” as well.
- 2.
Note the distinction between DI and DI types where the former refers to the data itself while the latter is about the type of data, where ‘age’ is a DI type and ‘68’ is a corresponding piece of DI.
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Acknowledgement
We would like to thank Murat Sensoy and Pinar Yolum for our fruitful discussions. This work was supported by the ITEA M2MGrids Project, ITEA141011.
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Aydoğan, R., Øzturk, P., Razeghi, Y. (2017). Negotiation for Incentive Driven Privacy-Preserving Information Sharing. In: An, B., Bazzan, A., Leite, J., Villata, S., van der Torre, L. (eds) PRIMA 2017: Principles and Practice of Multi-Agent Systems. PRIMA 2017. Lecture Notes in Computer Science(), vol 10621. Springer, Cham. https://doi.org/10.1007/978-3-319-69131-2_31
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