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

Author(s) : Adline Jancy

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.

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