Evaluating the Degree of Trust Under Context Sensitive Relational Database Hierarchy Using Hybrid Intelligent Approach

Abstract

Trust is a binary value either 0 or 1which is not measurable in real application. An entity can either trust another entity completely or do not trust at all. Trust between different entities in generalization-specialization relational model in database varies with respect to adjacent level of hierarchy. Trust value among entities depends not only on hierarchy level but also the context in which entities belong. In this paper the authors propose a model that allows evaluating trust relationships between two entities in the same context. Basically the trust depends on parameters like knowledge, experience and recommendation. In real application it is not always possible to have prior knowledge about mentioned entities. Extending this theory, it is shown that how the trust relationships is evaluated between different entities in different contexts of specialization level. As the trust represents uncertainty therefore, fuzzy logic is used to overcome the concept of binary value for trust. Considering the dynamic attributes of an entity based system, an appropriate agent based methodology could be incorporated. This paper introduced a model called FACO based on Fuzzy logic and Ant colony to calculate both the trust and the updated trust value among entities.

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