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

Article Computer Science, Information Systems

IoT Network Traffic Classification Using Machine Learning Algorithms: An Experimental Analysis

Rakesh Kumar et al.

Summary: IoT refers to a wide variety of embedded devices connected to the Internet, enabling them to transmit and share information in smart environments. Regular monitoring of IoT network traffic is crucial for proper functioning and detection of malicious activities, with classification of IoT devices in the network traffic being a key activity. Various machine learning algorithms are proposed for IoT traffic classification, but their accuracy depends on data sources, features extracted, and deployment locations. Identifying network traffic characteristics and suitable machine learning algorithms is important for accurate and optimized IoT traffic classification, with a comparative analysis of popular machine learning algorithms conducted in this study.

IEEE INTERNET OF THINGS JOURNAL (2022)

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Article Computer Science, Information Systems

Application-Oriented Traffic Modeling of WiFi-Based Internet of Things Gateways

Atef Abdrabou et al.

Summary: This article focuses on the traffic patterns of IoT devices sending data wirelessly to a gateway via WiFi. It found that different applications have different traffic patterns that can be modeled using specific probability distributions. The experimental results also showed that analyzing these distributions accurately predicts the delay performance of connecting the gateway to the cloud.

IEEE INTERNET OF THINGS JOURNAL (2022)

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Proceedings Paper Computer Science, Information Systems

An Accurate & Efficient Approach for Traffic Classification Inside Programmable Data Plane

Muhammad Saqib et al.

Summary: In-network traffic classification is a category of in-network computing, where an accurate network traffic classifier is deployed inside a programmable data plane to classify traffic at maximum speed while considering device constraints. Traffic flow can be classified using a single feature, sequential packet size information, to achieve accurate and early-stage network traffic classification with minimal use of networking device resources.

2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022) (2022)

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Article Computer Science, Hardware & Architecture

ByteSGAN: A semi-supervised Generative Adversarial Network for encrypted traffic classification in SDN Edge Gateway

Pan Wang et al.

Summary: With the rapid development of communication network technology, network traffic data types and quantities are increasing, making network traffic classification more important. SDN Edge Gateway, as the closest network element to users, can greatly enhance user experience through traffic classification capabilities. Utilizing GAN-based semi-supervised learning methods can improve traffic classification performance without the need for large labeled datasets.

COMPUTER NETWORKS (2021)

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Article Computer Science, Hardware & Architecture

Opt-ACM: An Optimized load balancing based Admission Control Mechanism for Software Defined Hybrid Wireless based IoT (SDHW-IoT) network

Rohit Kumar et al.

Summary: The widespread use of IoT necessitates integration of various wireless networking technologies, with future technologies like SDN providing solutions to challenges. This study presents an Opt-ACM based on optimized load balancing for network flow management to reduce congestion.

COMPUTER NETWORKS (2021)

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Article Computer Science, Information Systems

A Runtime-Enabled P4 Extension to the Open vSwitch Packet Processing Pipeline

Tomasz Osinski et al.

Summary: In this article, the authors introduce P4rt-OVS, an original extension of OVS that enables runtime programming of protocol-independent and stateful packet processing pipelines. P4rt-OVS extends the forwarding model of OVS with the userspace Berkeley Packet Filter (uBPF), bringing a new extensibility mechanism. The system also comes with a P4-to-uBPF compiler, allowing developers to write data plane programs in the high-level P4 language and inject them to the OVS packet processing pipeline at runtime.

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT (2021)

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Article Computer Science, Information Systems

Edge Intelligence Based Identification and Classification of Encrypted Traffic of Internet of Things

Yue Zhao et al.

Summary: The paper proposes a detection model of Internet of Things encrypted traffic based on edge intelligence, and introduces four new classification and identification methods for encrypted traffic. Experimental results show that these methods perform well in terms of accuracy and recall rates.

IEEE ACCESS (2021)

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Article Automation & Control Systems