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Artificial Neural Network-Based Mechanism to Detect Security Threats in Wireless Sensor Networks.

Shafiullah Khan^1,2, Muhammad Altaf Khan², Noha Alnazzawi³

¹College of Computing and Systems, Abdullah Al Salem University, Kuwait City 72303, Kuwait.

Sensors (Basel, Switzerland)

|March 13, 2024

Summary

This summary is machine-generated.

This study introduces an artificial neural network (ANN) method to detect routing attacks in wireless sensor networks (WSNs). The novel approach significantly enhances WSN security and data integrity against threats like black-hole and wormhole attacks.

Keywords:

artificial neural networks backpropagation routing attacks wireless sensor network

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Area of Science:

Computer Science
Cybersecurity
Network Engineering

Background:

Wireless Sensor Networks (WSNs) are critical for data collection in diverse fields but face significant security risks from routing attacks.
Vulnerabilities in WSNs can compromise network performance, data integrity, and sensitive information.
Existing security measures often struggle to adapt to evolving and novel routing threats.

Purpose of the Study:

To propose and evaluate a novel method for detecting routing attacks in WSNs.
To enhance the security and reliability of WSNs against sophisticated threats.
To leverage artificial neural networks for intelligent threat detection in resource-constrained environments.

Main Methods:

Utilized feed-forward artificial neural networks (ANNs) to model WSN behavior and identify routing attacks.
Trained and tested the ANN model using the heterogeneous CICIDS2017 dataset for robustness.
Employed the NS2 simulator for experimental validation and performance assessment.

Main Results:

The proposed ANN-based system achieved a high detection rate of 99.21% and accuracy of 99.49%.
Demonstrated superior performance in detecting known and novel routing attack patterns compared to existing methods.
Effectively minimized false positive rates, enhancing detection reliability.

Conclusions:

The developed ANN method offers a robust and effective solution for securing WSNs against routing attacks.
This approach significantly improves the security of wireless sensor networks, protecting sensitive data.
The study provides a reliable mechanism for secure communication in resource-constrained WSN environments.