  Internet of Things (IoT) occupies a vital aspect of our everyday lives. IoT
networks composed of smart-devices which communicate and transfer the
information without the physical intervention of humans. Due to such
proliferation and autonomous nature of IoT systems make these devices
threatened and prone to a severe kind of threats. In this paper, we introduces
a behavior capturing, and verification procedures in blockchain supported
smart-IoT systems that can be able to show the trust-level confidence to
outside networks. We defined a custom \emph{Behavior Monitor} and implement on
a selected node that can extract the activity of each device and analyzes the
behavior using deep machine learning strategy. Besides, we deploy Trusted
Execution Technology (TEE) which can be used to provide a secure execution
environment (enclave) for sensitive application code and data on the
blockchain. Finally, in the evaluation phase we analyze various IoT devices
data that is infected by Mirai attack. The evaluation results show the strength
of our proposed method in terms of accuracy and time required for detection.
