A community-aware approach for detecting network anomalies

Network anomalies can for for example be spammers in communication networks, intruders in physical network systems or bots on social media. Master student Thomas Helling developed a new algorithm for finding such spammers, taking the awareness of nodes with respect to the community structure of the network, into account. Thomas…

Counting temporal motifs in multilayer networks

Network motifs are small building blocks consisting of a handful of nodes. Complex networks are made up out of countless of these little network patterns. Master student Hanjo Boekhout worked on algorithms for efficiently counting these motifs in a large-scale multilayer setting in which multiple types of interaction between nodes…

Using network analysis to understand the role of software components

Software typically consists of a large number of components (in software design terms called ‘classes’). Master student Xavyr Rademaker worked on new ways of automatically determining the role of such a software component using a combination of machine learning and complex network analysis. This can be usefil, as it may…

New CNS Lab website

This is the very first post on the new Leiden CNS Lab website. In the future, this website will be updated with news and information on upcoming events and activities.