Towards a secure behavior modeling for IoT networks using blockchain

In recent years, Internet of Things (IoT) occupies a vital aspect of our daily lives. IoT networks composed of smart-devices which communicate and exchange the information without the physical intervention of humans. Due to such proliferation and autonomous nature of IoT systems make the devices more vulnerable and prone to a severe kind of threats. In this paper, we propose a behavior, capturing and verification procedures in Blockchainsupported smart-IoT systems that can show the trust-level confidence to outside networks. We proposed our own custom 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 provide a secure execution environment (enclave) for sensitive application code and data on blockchain. Finally, in evaluation, we analyze various IoT devices data that is infected by Mirai attack. The evaluation results demonstrate the ability of our proposed method in terms of accuracy and time required for detection.