Project Summary:

Software Defined Networking (SDN) and Network Functions Virtualization (NFV) are emerging technologies in the fields of telecommunications and networking. In combination, SDNFV introduces a programmable, dynamic, and flexible network topology. All network topologies are vulnerable to cyber-attack and the traditional protection against attack has been a perimeter defence approach tuned to the target topology. However, the perimeter defence is no longer valid with the dynamic nature of SDNFV and an increasing volume of virtual network appliances that can be introduced or removed from the network on-demand. In order to secure dynamic software-defined networks with virtualized functions, new detection and protection mechanisms are required.

Software-Defined Networking (SDN) introduces programmability and logically centralized control to the network while NFV provides the flexibility to deploy new services quickly to adapt to user requirements. This introduces the opportunity to scale network threat detection on-demand. Collaboration and cooperation between network security services within and across network domains can increase the effectiveness of threat detection and protection mechanisms.
The main goal of this PhD thesis is to investigate and derive techniques and algorithms to increase the efficiency and effectiveness of network threat detection by exploiting the access to granular network information enabled by SDN and NFV.

Contact details:

Supervisor Name: Dr. Sandra Scott-Hayward
Tel: +44 (0)28 9097 1898
QUB Address: Email: