The workshop "Statistical and computational challenges in networks and cybersecurity" will bring together researchers from a variety of areas including social network modeling, text mining, cybersecurity, malware/intrusion detection and fraud detection, and explore big data arising from networks. Invited presentations will include research in a variety of related areas:
- transactional data on a graph, with additional variables describing the nodes and/or the transactions.
- dynamic network structure
- social network models
- more realistic models for graph data
- cyber defense and anomaly detection
- community detection on graphs
- scaling of models and algorithms to massive data problems
Researchers in statistics, computer science, mathematics and engineering will be involved, reflecting the diversity of disciplines developing methods for the analysis of network data.
On Monday and Tuesday (May 4-5), Eric Kolaczyk of Boston University will present a 2-day short course based on his book "Statistical Analysis of Network Data" and its new companion volume "Statistical Analysis of Network Data with R". The workshop will take place Wednesday May 6 - Friday May 8. Participants may register for the short course, the workshop, or both events. In addition to invited presentations there will be a poster session. Some travel funding will be available for students.
The event is part of the Thematic Program on Statistical Inference, Learning, and Models for Big Data, organized by the Fields Institute in conjunction with CANSSI. The thematic program runs from January to June, 2015.