Qiskit Network Anomaly Detection

In this talk, I’ll demonstrate how we can harness quantum machine learning (QML) to detect network anomalies faster and more efficiently than traditional methods. Using Qiskit and the KDD Cup dataset, I’ll walk through building a quantum circuit-based classifier that identifies suspicious network patterns. I’ll explore how quantum circuits can be used for binary classification, the architecture of our enhanced quantum circuit with entanglement layers, practical techniques for data preprocessing and dimensionality reduction, performance optimization strategies for faster training and a demo of the system detecting network anomalies.