Network Intrusion Detection using Deep Learning

The book "Network Intrusion Detection using Deep Learning" provides a comprehensive overview of the latest advancements in Intrusion Detection System (IDS) technology using state-of-the-art deep learning methods. It covers both classical machine learning approaches and the latest developments in the field of deep learning. Notably, it highlights the applications of deep learning in various classes of IDS, including generative, discriminative, and adversarial networks. The book also compares different deep learning-based IDS using benchmark datasets and introduces two novel feature learning models: deep feature extraction and selection (D-FES) and a fully unsupervised IDS. At the end of the book, further challenges and research directions are discussed. This technical book is a valuable resource for students, researchers, and practitioners interested in deep learning and intrusion detection.