Software to detect network intrusions protects a computer network from unauthorized users, including perhaps insiders. This project aims to build an AI-basedn etwork Intrusion Detection System (IDS), a predictive model distinguishing between bad connections, called intrusions or attacks, and good normal connections.
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This project is an AI-based network Intrusion Detection System (IDS), a convolutional neural network model trained to distinguish between intrusions/attacks and normal connections.
The model is trained by generalizing the KDD Cup 1999 dataset. See full project report.
Contributors: Lucas Saechao. Ashley Thor. Noah Venethongkham.