In the Internet of Things based military environment, to achieve an assigned task without compromising security concern is a challenging task. Resource-constrained devices, Self-organized, disseminated nature of sensor nodes, unstable topology environment, open wireless medium, and shared network environment make IoT differ from other networks. All together leads to security threats to the IoT environment. The success of any IoT based application depends on effective communication among the devices that can be achieved by routing protocols. Typically, they designed to cope with fruitful communication but in effect, they might be targeted and affected by mischievous devices. Blackhole devices are such devices that aim to disturb the normal routing operations. But the identification of trusted devices that means authentication needs to be provided for successful task completion. At present, trust management plays an important part in prediction construction and appropriate for resource-strained devices. In this article, a multi-dimensional trust-based security model is proposed to guarantee authentication by avoiding blockhole devices based on direct, indirect, sense-making, social, and stereotypes. In addition, the q-learning mechanism is used to enhance the proposed method. The simulation study represents the applicability of the projected model.