Economic and social activity is increasingly reflected in operations on digital objects and network-mediated interactions between digital entities. Trust is a prerequisite for many of these interactions, particularly if items of value are to be exchanged. The problem is that automated handling of trust-related concerns between distributed entities is a relatively new concept and many existing capabilities are limited or application-specific, particularly in the context of informal or ad-hoc relationships. This thesis contributes a new family of probabilistic trust metrics based on Network Reliability called the Generic Reliability Trust Model (GRTM). This approach to trust modelling is demonstrated with a new, flexible trust metric called Hop-count Limited Transitive Trust (HLTT), and is also applied to an implementation of the existing Maurer Confidence Valuation (MCV) trust metric. All metrics in the GRTM framework utilize a common probabilistic trust model which is the solution of a general reliability problem. Two generalized algorithms are presented for computing GRTM based on inclusion-exclusion and factoring. A conservative approximation heuristic is defined which leads to more practical algorithm performance. A JAVA-based implementation of these algorithms for HLTT and MCV trust metrics is used to demonstrate the impact of the approximation. An XML-based trust-graph representation and a random power-law trust graph generator is used to simulate large informal trust networks.
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/611 |
| Date | 10 April 2008 |
| Creators | Mahoney, Glenn R. |
| Contributors | Myrvold, W. J.|Shoja, Gholamali C. |
| Source Sets | University of Victoria |
| Detected Language | English |
Page generated in 0.0017 seconds