Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Internet of Things (IoT) is a popular social network in which devices are virtually connected for communicating and sharing information. This applied greatly business enterprises government sectors delivering the services to their customers, clients citizens. But, interaction successful only based on trust that each device has another. Thus very much essential network. As have access over sensitive information, it urges many threats lead data management risk. issue addressed by help take decision about trustworthiness requestor provider before communication sharing. Several trust-based systems existing different domain using Dynamic weight method, Fuzzy classification, Bayes inference few Regression analysis IoT. The proposed algorithm Logistic Regression, provide strong statistical background prediction. To make our stand regression support trust, we compared performance with equivalent sound Beta distribution. studied simulated IoT setup Quality Service (QoS) Social parameters nodes. model performs better terms various metrics. An connects heterogeneous such as tags sensor information avail application services. most salient features system design scalability, extendibility, compatibility resiliency against attack. works finds way integrate direct indirect converge quickly estimate bias due attacks addition above features.