Analysis of data trust through an intelligent–transparent–trust triangulation model. Issue 3 (22nd May 2018) - Habib, Sami J.; Marimuthu, Paulvanna N.
Abstract: Computing sensor systems are involved in making vital decisions based on sensed data. Thus, the data need to be trustworthy. We have made a novel attempt to analyse the trustworthiness of computing sensor systems outcomes by modelling trust as an association triangle between intelligence, transparency, and trust. Intelligence represents the computing algorithm, which makes the vital decisions, and transparency represents completeness by explicitly specifying the decision‐making process. We propose a triangulation model as a framework for assessing the trust, and we have selected 2 trust factors analogous to transparency and intelligence: the deviation of malfunctioning sensor data from its neighbours and the deviation from its own history. We have derived a set of relationships between the trust factors and their outcomes, and we have associated them with the proposed triangulation model. We also have formulated the generation of a trust subspace as an optimization problem with an objective function to maximize the trust. We have employed Tabu Search combined with Simulated Annealing to search for the best possible weighted combinations of trust factors. We have projected the experimental results onto a 3‐coordinate equilateral triangle to validate the decision analysis by displaying a definite trust or untrustworthiness of data.