In recent years, we have witnessed an increasing use of trust and reputation systems in different areas of ICT. The idea at the base of trust and reputation systems is of letting users to rate the provided services after each interaction. Other users may use aggregate ratings to compute reputation scores for a given party. The computed reputation scores are a collective measure of parties trustworthiness and are used to drive parties interactions.
Due to the widespread use of reputation systems, research
work on them is intensifying and several models have been
proposed. This calls for a methodology for the analysis and
the evaluation of trust and reputation systems that can help
researcher and developers in studying, designing and implementing such systems. In this thesis we propose different kinds of theoretical results and software tools that could be useful means for researchers and developers in area of trust and reputation systems.
Our work addresses the three main stages of trust and reputation systems development, namely study, design and implementation. We provide: 1) a general framework based
on Bayesian decision theory for the assessment of trust and
reputation models, 2) an analysis methodology for reputation
systems based on a coordination language, 3) a software tool
for network-aware evaluation of reputation systems and their
rapid prototyping
