Patrik Goldschmidt
Position: Network Intrusion Detection Using Machine Learning
Supervising team: Daniela Chudá (KInIT)
The research focuses on the detection of computer network anomalies and intrusions utilizing machine learning techniques. Instead of following the classical “better model, better results” style, we rather decided to adopt a data-centric approach to the problem. This way, we expect to improve the practical usability of intrusion detection systems by improving data quality rather than creating and fine-tuning complex machine learning architectures.