Seminar Network Traffic Analysis using Deep Packet Inspection and Data Visualization – Bram Cappers
Each month a Guest Hacker Program is being organized at KPN. For this program KPN Chief Information Security Office (CISO) invites prominent experts from the security industry to tell their story. In the past, Phil Zimmermann, Martin Roesch, Mikko Hyponnen and Karsten Nohl spoken here. The event is free to attend for everyone who is interested, please make sure to register.
Network Traffic Analysis using Deep Packet Inspection and Data Visualization – Bram Cappers
For the protection of (critical) infrastructures against complex virus attacks, deep packet inspection is unavoidable. In our project SpySpot we are developing new tools and techniques to assist analysts in gaining insight and reverse engineering network traffic. Discovery of computer viruses or suboptimal resource usage in the traffic for instance can assist analysts in debugging, protecting, and optimizing their system.
In this presentation we will discuss the role of visualization to improve network intrusion detection and anomaly detection in cyber security. In addition, we present a demo of a new data visualization system called Eventpad to study network traffic by visualizing patterns according to user-defined rules. We illustrate the effectiveness of the system on real-world Voice over IP traffic.
Bram Cappers is a PhD student at Eindhoven University of Technology.
He achieved both his bachelor and master’s degrees in Computer Science (with honors) at Eindhoven University of Technology. After obtaining his Master in 2014 he started as a PhD student in the area of data visualization and cyber security.
In their project SpySpot they are developing new tools and techniques to assist analysts in gaining insight and reverse engineering network traffic. He has recently won a Visual Analytics Science and Technology award for the discovery of patterns and anomalies in traffic data and is active in the program committee of the IEEE Symposium on Cyber Security Visualization.