Lattice-based ranking for service trust behaviors

In service-based communities, services strive to collaborate to successfully perform their tasks. In this context, trust is becoming a paramount factor in deciding whether or not to interact with a service. In this paper, we deal with trust from the perspective of behavior analysis and propose a novel feature-based approach for the ranking of trust behaviors. We represent the trust behavior of a service by a sequence of trust observations collected over a certain time frame, called the trust sequence. Our approach spans over a lattice-based trust ranking algorithm for trust sequences, called LattRank. LattRank is inspired by the top-down breadth-first traversal of an attribute-value lattice. It assigns to each trust sequence a ranking score based on the trust order constraints. The ranking score indicates to which extent a service is stable in the trustworthy behavior. We prove formally the correctness of LattRank and evaluate it using ranking evaluation metrics through a comprehensive experimental study.