Quantum-Enhanced Edge Computing for Robust Cyber Threat Detection
S. Anand · 2025
The growing complexity of cyber threats has surpassed traditional detection systems, especially where real-time response and distributed protection are vital. This chapter explores a hybrid Quantum-Edge framework for cyber threat detection. Quantum Computing's parallelism and advanced data processing capabilities complement Edge Computing's low-latency, decentralized analysis. Our framework integrates quantum feature transformation, quantum-enhanced anomaly detection, and federated learning on edge nodes. Using Qiskit, simulated attacks, and real-time edge processing, we demonstrate improved detection accuracy, lower false positives, and faster responses. We also propose future directions in quantum-resilient, privacy-preserving, and scalable cybersecurity solutions.