Adaptive Defense Zero-Day Attack Detection in NIDS with Deep Reinforcement Learning

5,500.00

Aim:

Ā  Ā  Ā  Ā  Ā  Ā  Ā Design and deliver a lightweight, adaptive, and high-generalization intrusion detection framework that accurately identifies zero-day and known cyberattacks in network traffic while maintaining efficient real-time performance.

 

Fairness-Oriented Charging Station Location Optimization Driven by Deep Reinforcement Learning

5,500.00

Aim:

Ā Ā Ā Ā Ā Ā Ā  Ā Ā Ā  The aim of this project is to develop a fairness-oriented EV charging station location optimization framework using geospatial analytics and deep reinforcement learning. It integrates population density, POI distribution, and spatial coverage to identify high-impact candidate sites. The system ensures region-balanced accessibility while maximizing demand-weighted service coverage.