AI-based Intelligent SDN Controller to Optimize Onion Routing Framework for IoMT Environment
Malaram Kumhar, Jitendra Bhatia, Nilesh Kumar Jadav, Rajesh Gupta, Sudeep Tanwar · 2023
The Internet of medical things (IoMT) faces tough considerations regarding security and reliability in data transmission. In recent years, the main networking concerns that have drawn a lot of attention have been Software Defined Networking (SDN), Machine Learning (ML), and onion routing (OR). The impact of Internet of things (IoT) has transformed all fields of life, but it has significantly affected the healthcare industry. In IoMT, the data is transmitted via energy-constrained, low-power IoT sensors with security and privacy issues. This paper addressed the various security issues and employed onion routing to overcome those issues. Software-defined network (SDN) controller and ML techniques are adopted to classify the request received from various applications/industries to voluntarily add their routers in the onion routing network, strengthening the anonymity in the onion routing network. This paper discusses the onion routing process to securely send the patient's health data from the source node to the target node. We designed an AI-enabled onion routing to retain the anonymity of the data. Moreover, a centralized SDN controller categorizes the malicious and non-malicious routers involved in IoMT data transmission. The simulation results demonstrate that the suggested AI module based on the SDN framework outperforms the traditional security mechanism. The proposed approach with SDN and AI is quite efficient and achieves 97.23% accuracy for identifying the malicious nodes in onion-based routing.