International Journal of Research and Development in Engineering Sciences (IJRDES ) | A Hybrid Cnn and Decision Tree Based Intrusion Detection System For Secure Wireless Sensor Networks

A Hybrid Cnn and Decision Tree Based Intrusion Detection System For Secure Wireless Sensor Networks

The By employing a machine learning algorithm to analyse traffic and identify intrusions, intrusion detection systems assist in identifying damaging hostile attacks in wireless sensor networks. The RSA encryption method is used to boost the performance of the wireless sensor network while also improving the security of data transmission. The goal of this research is to develop a hybrid algorithm for network intrusion detection in wireless sensor networks. This approach combines the principles of decision tree, convolutional neural networks (CNNs), and RSA encryption. Through the integration of these cutting-edge techniques, a comprehensive security solution for crucial applications is offered. This integration improves not only the detection and prevention of intrusions but also guarantees the confidentiality and integrity of sensitive data transmitted across wireless sensor networks.

Research Type: Field Research
Paper Type: Case Study Paper
Vol.7 , Issue 2 , Pages: 33 - 39, Mar 2025
Published on: 20 Mar, 2025
Issue Type: Regular

Cite Score

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100
No. of authors

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75
No. of Downloads

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43

Cite Score

:

100
No. of authors

:

75
No. of Downloads

:

43

Cite Score

:

100
No. of authors

:

75
No. of Downloads

:

43

About Authors:

Adline Jancy

India

Viswam Engineering College

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*Corresponding Author: Adline Jancy, adlinjan@gmail.com

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Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.