PiGateway: Real-time granular analysis of smart home network traffic using P4

The Internet of Things (IoT) makes the home smarter by real-time sensing of the situation and transmission of data to the cloud. As IoT devices continue to expand rapidly, a critical need arises for effective device -type identification methods. Accurate identification of IoT device types is essential for various applications, including network management, security, etc. To identify the type of IoT devices, existing works have proposed various Media Access Control (MAC)-based and Machine Learning (ML) approaches. These solutions lack real-time granular analysis and In-network classification of IoT traffic. In this work, we propose PiGateway: a P4-based gateway to classify the type of IoT devices at a line rate and prioritize the device type. Initially, PiGateway develops a Decision Tree (DT) model and generates flow rules from the model. The developed model is deployed in the PiGateway using two mechanisms. One mechanism is to convert the DT model into Match-Action Tables (MATs), where the tables store the flow rules. Another approach developed an optimized model by deploying the DT model into PiGateway as a mathematical expression. Further, to achieve the In-network classification, the gateway calculates flow-level features dynamically from incoming IoT traffic flow. The feature values are given as input to the deployed DT model for classifying the flow into a specific device type. Subsequently, the flow is prioritized based on device type and Type of Service (ToS) field value. Additionally, our proposed solution is designed and tested in a real-time environment. Through implementation results, we show that the PiGateway can classify the type of IoT devices with 98.61% accuracy and an average CPU usage of 10.68%. Also, the classification time in PiGateway is 0.098ms for 8000 flows using an optimized model. Finally, the proposed system serves as a gateway in a smart home IoT network.

Automated summary

The Internet of Things (IoT) enables real-time sensing and data transmission to make homes smarter. Effective device-type identification methods are crucial as the number of IoT devices continues to grow. In this paper, a P4-based gateway called PiGateway is proposed to classify and prioritize the type of IoT devices. By utilizing a decision tree model and flow rules, PiGateway enables real-time granular analysis and in-network classification of IoT traffic.