Refined Convolutional Network for Intrusion Detection System

With the rapid growth of network technologies and the corresponding increase in cyber threats, ensuring the security of network systems has become paramount. IDS play a vital role in identifying and mitigating malicious activities within network traffic. This research paper proposes an advanced IDS utilizing an Improved Convolutional Neural Network to enhance detecting with more accuracy and efficiency. Proposed system aims to detect a larger range of attacks with high precision, addressing the limitations of standard machine learning methods. Through extensive experimentation on benchmark datasets, the ICNN demonstrates higher performance in detecting both known and novel threats, making it a robust solution for modern cybersecurity challenges.