Robust Big Data Analytics for Intrusion Detection in IoT Network
Lightning Talk
In the current digital era, network security has become a paramount concern due to the exponential increase in network traffic and the corresponding rise in cyber threats, especially within IoT networks. Network Intrusion Detection Systems (NIDS) play a crucial role in identifying and mitigating these threats. This work presents a robust big data analytics framework for NIDS that integrates multiple machine learning algorithms to enhance detection accuracy and robustness through a comprehensive three-step process: preprocessing, feature engineering, and stacking.
