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Trust Modeling with Context Representation and Generalized Identities (2007)
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BibTeX
@MISC{Rehák07trustmodeling,
author = {Martin Rehák and Michal Pěchouček and Milos Gregor},
title = {Trust Modeling with Context Representation and Generalized Identities},
year = {2007}
}
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Abstract
The majority of existing trust models is based on three underlying assumptions: (i) proven identity of agents, (ii) repetitive interactions and (iii) similar trusting situations. In our work, we address these assumptions by introduction of simple classification techniques in our mechanism that extends existing trust models, rather than by introduction of a new model. The proposed approach formalizes the situation (context) and/or trusted agent identity in a multi-dimensional Identity-Context space, and attaches the trustworthiness evaluations to individual elements from this metric space, rather than to fixed identity tags (e.g. AIDs, addresses). Trustworthiness of the individual elements of the Identity-Context space can be evaluated using any trust model that supports weighted aggregations and updates, allowing the integration of the mechanism with most existing work. Trust models with the proposed extension are appropriate for deployment in dynamic, ad-hoc and mobile environments, where the agent platform can not guarantee the identity of the agents and where the cryptography-based identity management techniques may be impractical due to the unreliable and costly communication.
Keyphrases
trust model context representation generalized identity individual element weighted aggregation repetitive interaction cryptography-based identity management technique agent identity costly communication mobile environment multi-dimensional identity-context space identity tag underlying assumption identity-context space new model agent platform trustworthiness evaluation metric space simple classification technique
