LEMDA: A Novel Feature Engineering Method for Intrusion Detection in IoT Systems

arXiv:2404.16870v1 Announce Type: cross
Abstract: Intrusion detection systems (IDS) for the Internet of Things (IoT) systems can use AI-based models to ensure secure communications. IoT systems tend to have many connected devices producing massive amounts of data with high dimensionality, which requires complex models. Complex models have notorious problems such as overfitting, low interpretability, and high computational complexity. Adding model complexity penalty (i.e., regularization) can ease overfitting, but it barely helps interpretability and computational efficiency. Feature engineering can solve these …

abstract arxiv communications connected devices cs.ai cs.cr cs.lg data detection devices dimensionality engineering feature feature engineering internet internet of things iot massive novel systems type