Trust and privacy management support for context-aware service platforms

Abstract

In a context-aware service platform, service providers adapt their services to the current situation of the service users using context information retrieved from context information providers. In such a service provisioning platform, important trust and privacy issues arise, because different entities responsible for different tasks have to collaborate in the provisioning of the services. Context information is privacy sensitive by nature, making the communication and processing of this information a potential privacy threat. The main goal of this thesis is to learn how to support users and providers of context-aware services in managing the trade-off between privacy protection and context-based service adaptation. More and more precise context information retrieved from trustworthy context information providers allows context-aware service provider to adapt their services more reliably. However, more and more precise context information also means a higher risk for the service users in case of a privacy violation

The Rhadamanthys Quality of Context Architecture

“…The definition of trustworthiness found in it differs from what is shown in [Buchholz et al 2003] and [Sheikh et al 2008]. The latter two consider trustworthiness to be a QoC attribute, but [Neisse 2012] considers it to be "a property of the context provider from the context consumer's point of view, and is not a quality concept related to the context information itself" [Neisse et al 2008]. Thus, trustworthiness is treated in the Trust Management Model and defined there instead of being defined in the QoC Model.…”

“…In Trust and Privacy Management Support For Context-Aware Service Platforms [Neisse 2012], QoC criteria are identified as QoC attributes, and are defined based on an international metrology standard found in [Vim 2004]. The QoC model defined in that work allows QoC values, such as precision of context information values and freshness of timestamps, to be obtained implicitly.…”

From Ambient Sensing to IoT-based Context Computing: An Open Framework for End to End QoC Management

“…The uncertainty is an interval expressed in the same unit as the measurement. Precision qualifies “how close together or how repeatable the results from a measurement are” [ 10 ]. Precision is expressed in percent.…”

QoCIM: A Meta-model for Quality of Context

“…Neisse 2012 [12] suggested in 2012 to adapt the ISO standard used in metrology to define QoC criteria. He established that the concepts of accuracy and precision used as QoC criteria are just an approximative definition of the precision criterion used in metrology.…”