VANET has become a live field of study, standardization, and elaboration because it has massive potential to enhance vehicle and road safety, traffic effectiveness, and convenience as well as accommodation to both motorist and passengers. Recent research efforts have placed a strong accent on novel VANET design architectures and implementations. A lot of VANET research work have axis on concrete areas including routing, broadcasting, Quality of Service (QoS), and safety. In VANETs, due to the characteristics such as openness and dynamic topology, networks suffer from various attacks in the data plane. Even worse, some attacks can subvert or bypass the frequently used identity-based security mechanisms. To secure the data plane of VANETs, trust management system was proposed. An attack resistant trust management scheme is capable of detecting malicious attacks and also deals with it. It also calculates the trustworthiness of both data node and mobile node in VANETs. But the issues were that the model is considering trust factor only to find route from source to the destination. The acquired route on the basis of single parameter has proven to be ineffective and less trust worthy. Moreover, the designed system takes decision manually on the basis of threshold value and decision taken manually can be inappropriate at several points. Considering this fact, the existing system is concluded as less trust worthy and ineffective in terms of transmission of data. In this paper, the manual decision making process of ART scheme is replaced with artificial intelligence system i.e. fuzzy deduction system to evaluate the selection rate of individual node in the network. In addition to this, FDS grouping approach is initiated in novel method to group the nodes and based on the maximum selection rate in individual group; a node will be selected for the transmission of data. This criterion will enhance the level of security with reduction in error rate while selecting relay node.
