Big Data Security Analytics for the Internet of Things
The main objective of this research project is to design an anomaly detection algorithm to mine network traffic data represented in the form of dynamic attributed graphs. The first step of the project is to investigate the feature selection of the different attributes for a robust and efficient representation of the network data in the graph. This will be followed by the development of a global anomaly detection algorithm that will highlight anomalous data samples in the dynamic graph. Finally, a deeper inspection of the anomalous data sample will be performed to determine the type of anomaly and further classify it if necessary. We envisage applying the developed algorithm to intrusion detection for cyber-physical networks such as SmartGrid and Smart Transport.
How to Apply
Applicants should apply electronically through the Queen’s online application portal at: https://dap.qub.ac.uk/portal/