Ramalakshmi Alagarsamy

A Scalable Deep Learning-Based Intrusion Detection System for Real-Time Cybersecurity in IoT Networks of the Sugar Industry

The design and implementation of a scalable, real-time Intrusion Detection System using deep learning-based Stacked Ensemble models, including CNN-LSTM, AE-RF, XGB-DNN and LSTM-Bagging, to detect and mitigate severe cyber-attacks such as DDoS, Ransomware and Man-in-the-Middle (MITM).