Data Analysis for Network Cyber-Security

This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research.Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches.

Table of Contents

Chapter 1. Inference for Graphs and Networks: Adapting Classical Tools to Modern Data
Chapter 2. Rapid Detection of Attacks in Computer Networks by Quickest Changepoint Detection Methods
Chapter 3. Statistical Detection of Intruders Within Computer Networks Using Scan Statistics
Chapter 4. Characterizing Dynamic Group Behavior in Social Networks for Cybernetics
Chapter 5. Several Approaches for Detecting Anomalies in Network Traffic Data
Chapter 6. Monitoring a Device in a Communication Network