Network intrusion detection with Deep Learning

Network intrusions and computer attacks affect production systems and people’s everyday life. In recent years, such cyber-crimes have become more difficult to detect with traditional signature-based approaches, due to the availability of many attack techniques. In this context, Deep Learning (DL) has shown high potential in many fields of network security, including network intrusion detection.
This course will lead the students through many aspects related to the implementation of a DL-based Network Intrusion Detection System (NIDS), starting from the analysis of the properties of malicious network traffic, to the design and tuning of a neural network model, and to understanding the challenges of deploying a NIDS in real-world settings.