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The Guardian Node Slow Dos Detection Model For Real-time Application In Iot Networks.

Home
The Guardian Node Slow Dos Detection Model For Real-time Application In Iot Networks.

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The Guardian Node Slow DoS Detection Model for Real-Time Application in IoT Networks.

Andy Reed¹, Laurence Dooley¹, Soraya Kouadri Mostefaoui¹

¹School of Computing and Communications, The Open University, Walton Hall, Milton Keynes MK7 6AA, UK.

Sensors (Basel, Switzerland)

|September 14, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

A new Guardian Node model detects Slow Denial of Service (DoS) attacks in real-time on Internet of Things (IoT) networks. It achieves over 98% accuracy with significantly lower resource overheads than traditional machine learning methods.

Keywords:

guardian node internet of things slow DoS slow HTTP get slow post slow read

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Design and Analysis for Fall Detection System Simplification

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Published on: April 6, 2020

Area of Science:

Cybersecurity
Network Security
Internet of Things (IoT) Security

Background:

Slow Denial of Service (DoS) attacks target application layer services like HTTP, evading traditional detection.
Existing machine learning (ML) and artificial intelligence (AI) methods lack real-time detection and are computationally intensive for resource-constrained IoT networks.
Slow DoS attacks mimic legitimate traffic, making them difficult to distinguish from genuine nodes with poor connectivity.

Purpose of the Study:

To introduce an innovative Guardian Node (GN) model for real-time Slow DoS attack detection in IoT environments.
To develop a detection mechanism that is computationally efficient and suitable for resource-scarce IoT networks.
To accurately differentiate malicious Slow DoS traffic from legitimate traffic and normal network anomalies.

Main Methods:

The Guardian Node (GN) model analyzes packet length and packet delta time in real-time.
The GN operates within a narrow window of these two network attributes to identify Slow DoS variants.
The model is designed to distinguish attack traffic from genuine nodes with high latency or poor connectivity.

Main Results:

The GN model achieved real-time detection accuracies exceeding 98% across various traffic profiles.
The model successfully detected all three main variants of Slow DoS attacks, even under stealthy conditions.
Computational and storage overheads were over 96% lower compared to full packet capture techniques.

Conclusions:

The Guardian Node (GN) model offers a highly accurate and resource-efficient solution for real-time Slow DoS attack detection in IoT networks.
Its performance is comparable to existing ML approaches but with significantly reduced overheads, making it ideal for IoT deployment.
The GN provides a reliable method to protect IoT services from sophisticated application-layer attacks.