Negotiation for incentive driven privacy-preserving information sharing
| Autor: | Pinar Öztürk, Reyhan Aydoğan, Yousef Razeghi |
|---|---|
| Přispěvatelé: | Özyeğin University, Aydoğan, Reyhan, Razeghi, Yousef |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Knowledge management
Process (engineering) Computer science media_common.quotation_subject 02 engineering and technology Computer security computer.software_genre Negotiation Domain (software engineering) 020204 information systems 0202 electrical engineering electronic engineering information engineering Incentive-driven Data and information sharing Architecture media_common business.industry Information sharing Secrecy and privacy risk Incentive Privacy-preserving agent systems Ask price Position (finance) 020201 artificial intelligence & image processing business computer |
| Zdroj: | PRIMA 2017: Principles and Practice of Multi-Agent Systems ISBN: 9783319691305 PRIMA |
| DOI: | 10.1007/978-3-319-69131-2_31 |
| Popis: | Due to copyright restrictions, the access to the full text of this article is only available via subscription. 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. ITEA M2MGrids Project |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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