Cyber-Security project “Forecasting Zero-Day vulnerabilities using ML” (Prep, Samp, GA)

• Compared two final Pipelines, one with an 85% lower computational cost than the other
• Pipeline 1 outperformed Pipeline 2 when provided with equal computational resources
• Obtained 99% accuracy and achieved superior results with less training generations (5 vs 15)