Next–Generation Intrusion Detection for IoT EVCS: Integrating CNN, LSTM, and GRU Models

Federated Learning with 1D-CNN for Web Attack Detection on Edge-IIoTset using the Flower Framework. This project explores both IID and Non-IID data partitions to evaluate federated performance in decentralized IoT environments.

Machine Learning and Deep Learning Models for Web Attack Detection on the Edge-IIoTset Dataset. This repository explores and compares various classification architectures—including LightGBM, 1D-CNN, MobileNet-1D, etc.—optimized for deployment in edge computing environments.

HAC-IDS: Leakage-Aware Semantic Harmonization and Few-Shot Calibration for Cross-Dataset Intrusion Detection in Heterogeneous IoT/IIoT Environments