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Users trust assessment based on their past behavior in large scale collaboration

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Abstract

In a large scale peer-to-peer collaboration where control over data is given to users who can decide with whom to share their data, a main challenge is how to compute trust in the collaborators. In this paper we show how to automatically compute users trust according to their past behavior during the collaboration in order to be able to predict their future behavior. We focus on two use cases: contract-based multi-synchronous collaboration and trust game from game theory. We show that computing trust from a single interaction between two users depends on the application domain, but that a general methodology for aggregating trust during the successive interactions between two users can be applied for both use cases.
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Dates and versions

hal-03469344 , version 1 (07-12-2021)

Identifiers

  • HAL Id : hal-03469344 , version 1

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Claudia-Lavinia Ignat, Quang-Vinh Dang. Users trust assessment based on their past behavior in large scale collaboration. ICCP 2021 - IEEE 17th International Conference on Intelligent Computer Communication and Processing, Oct 2021, Cluj-Napoca/Online, Romania. ⟨hal-03469344⟩
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