Hybrid Quantum–Neural AI Defense
Welcome to a graduate capstone project developed as part of the Master of Science in Cybersecurity program at American Public University System (APUS). This website presents applied research completed for ISSC698 – Cybersecurity Studies: Capstone Practical, under the instruction of Professor Dr. Mimi Tam.
Hybrid Quantum–Neural AI Cybersecurity
Managerial cybersecurity capstone on hybrid quantum–neural AI for predictive cyber threat detection, adversarial resilience, and executive decision-making.
Explore the Project
The project, Design of Hybrid Quantum–Neural AI Systems for Predictive Cyber Threat Detection and Adversarial Resistance, explores how advanced artificial intelligence and emerging quantum computing techniques can be integrated to strengthen modern cybersecurity defenses. The focus is on predictive threat detection, adversarial resilience, and translating complex technical results into actionable insights for managerial and executive decision-making.
Solution & Architecture
Explore the system architecture for hybrid quantum–neural AI cybersecurity, including workflows, repository structure, and predictive defense design.
Simulation Lab
Step-by-step simulation of hybrid quantum–neural AI models for predictive cyber threat detection and adversarial resistance.
Business Impact & ROI
Executive analysis of cybersecurity ROI, cost-benefit tradeoffs, and monetization opportunities using hybrid quantum–neural AI systems.
Executive & Research Summary
Graduate-level executive summary of a hybrid quantum–neural AI cybersecurity capstone, including research findings and managerial insights.