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The project presents an AI-based network intrusion detection system utilizing Generative Adversarial Networks (GANs) to enhance the detection of cyber attacks. By generating synthetic attack data and employing XGBoost for classification, the system addresses the limitations of traditional intrusion detection methods. It achieved a 96.2% accuracy rate and is applicable in various sectors including banking and IT.

Author
prathish630
Language
EN

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