Job Details
Job Title
R&D on Intelligent In-Network Security Provisioning for Beyond 5G Systems
Job Type
Master Thesis Work, Doctoral Thesis Work, or Postdoctoral Research
Job Start Time
Immediately available
Job Duration
Negotiable, Depends on the Job Type.
Place of Work
Centre for Wireless Communications (CWC) – Networks and Systems, Faculty of Information Technology and Electrical Engineering, University of Oulu, Oulu, Finland.
Job Background
The vital importance of securing beyond 5G systems while meeting their stringent performance requirements has promoted the recent shift towards fully automated and smart security management. However, the current security management approaches are adopting a defense model where the intelligence related to detection and mitigation of security issues is logically centralized in the control and management plane, inducing extra network signaling and communication delays, and an increased risk of data privacy breaches. Thus, a new defense model that can handle security inside the network (i.e., at the data plane) in a fully distributed, autonomous, and adaptive way is vital to cater to performance, scalability and privacy demands for future mobile networks. To meet this goal, it is required to build an intelligent in-network security orchestration and management framework that allows security enforcement and defense at line-rate by embedding autonomic security closed-loops at the data plane and that is capable of dynamically and strategically provisioning and deploying security services according to the context and the agreed SAL and SSLA requirements for the deployed beyond 5G services. Emerging AI/ML techniques (particularly, Federated Learning, Deep Reinforcement Learning, and Edge AI) and Programmable Data Planes are key enabling technologies to build the capabilities of the envisioned framework.
Job Requirements
We are looking for highly-motivated students (or postdoc researchers) who are willing to conduct high-quality research works, developing efficient approaches and methods that leverage zero-touch management concept, AI/ML techniques, SDN/Programmable Data Planes technologies for enabling autonomic in-network security orchestration in beyond 5G networks. We are seeking candidates with good analytical skills and relevant experience in any of the following: machine learning, mathematical optimization, software-defined network, and network security. The potential candidates should have expertise in programming languages (Python, C/C++, Java), ML frameworks (Tensorflow, Keras, PyTorch), and SDN technologies (e.g., ONOS or OpenDayLight, P4).
Inquiry:
Should you have any inquiry, please contact Dr. Chafika Benzaid at Chafika.Benzaid@oulu.fi.
Application Form