Secure IoT Middleware Using SDN and Intent-Based Routing

With the rapidly increasing volume of IoT devices in the last decade due to the adaptation of the smart home/office concepts around the world, IoT devices are being targeted by hackers to perform attacks like DDOS and most likely creating botnets which will drastically decrease the performance of IoT devices and may also compromise the networks they are connected to. It is difficult to detect compromised IoT devices because there is more than one device in a simple IoT network, and it is difficult to monitor every device in the network. To solve this issue, this research proposes a Secure Middleware for IoT devices that will collect data generated by IoT devices, scan them for any malicious activity and then trigger an alert if any threat is detected in the IoT Network. The secure middleware is implemented in the proposed SDN architecture that uses Fog Computing, Cloud Computing, and VPN technologies to create a secure, scalable, flexible, and fast network architecture. A machine learning model is used to examine and detect any malicious activity in the IoT network. An open-source SIEM called the ELK stack is used to trigger alerts for the malicious activity identified by the ML model. With the help of the ML model and the SIEM, this proposed middleware will efficiently secure the IoT SoftwareDefined network by detecting malicious attacks in real-time.