Tuning Evidence-Based Trust Models

Eugen Staab, Thomas Engel, 2009 IEEE International Conference on Information Privacy, Security, Risk and Trust (PASSAT 2009), 2009.

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Abstract: Many evidence-based trust models require the adjustment of parameters such as aging- or exploration-factors. What the literature often does not address is the systematic choice of these parameters. In our work, we propose a generic procedure for finding trust model parameters that maximize the expected utility to the trust model user. The procedure is based on gametheoretic considerations and uses a genetic algorithm to cope with the vast number of possible attack strategies. To demonstrate the feasibility of the approach, we apply our procedure to a concrete trust model and optimize the parameters of this model.

Bibtex:

@inProceedings{staab09tuning,
author = {Eugen Staab and Thomas Engel},
title = {Tuning Evidence-Based Trust Models},
booktitle = {Proc. of the 2009 IEEE Int. Conf. on Information Privacy, Security, Risk and Trust (PASSAT ‘09)},
publisher = {IEEE Computer Society},
year = {2009},
month = {August},
pages = {92–99},
isbn = {978-0-7695-3823-5},
}

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