PDF - Security Intelligence in Emerging Networks - QC-132

Preferred Disciplines: Computer Engineering, Post-Doc Fellow
Company: Ericsson Canada Inc
Project Length:  2 years (6 units)
Desired start date: As soon as possible
Location: St Laurent, Quebec
No. of Positions: 1
Preferences: The candidate should be curious, ready to learn, passionate in the area of emerging networks, like mobility/5G, content delivery networks, IoTs, edge computing , cloud as well as software defined network and network function virtualization. Familiarity with machine learning and artificial intelligence is an asset. In addition, the candidate should have a good knowledge in computer and network security. The candidate should also be autonomous to a certain degree, ready to deliver results as needed and being passionate about the research in an industrial environment. The candidates with the academic or industrial background who show case abilities to realize prototypes and publish scientific papers, are encouraged. Language: Bilingual or English

About Company:

Ericsson as a major international telecom operator, and one of the top ten R&D investors in Canada, is both cloud service provider and cloud user. As a cloud service provider, investing over a billion dollars in building a massive ICT R&D center in Quebec, it is very important for Ericsson to have contingency plans for Disaster Recovery in place. Ericsson has also demonstrated its corporate responsibility for energy efficient and green solutions based on a long history of research in energy consumption and Life Cycle Assessment (LCA).

Project Description:

With all changes in information technology infrastructure, the networking evolves rapidly. Industrial parties focus more and more on softwarization of network. As such, some key trends are noticed: (1) democratization of software defined hybrid (wired and wireless) wide area networks, (2) Automation and orchestration, where artifacts like Docker and Kubernetes allow to provision networking elements, (3) Private and public cloud connectivity, where companies want to shift workloads from public cloud to private data-centers, (4) visible analystics, the data is pulled from virtualized network equipments to create telemetry analyzer points of presence. In the prevailing of these facts, network security properties (authentication, authorization, availability, integrity and privacy) need to be heavily reconsidered and re-evaluated. Thus, we aim to settle a research activity, which will cover the following themes:

  • Study of threats landscape in emerging networks
  • Leveraging collected data to create an intelligence model to detect malicious activities in emerging networks
  • Adapt the threats detection to emerging networks

Background and required skills

Research Objectives/Sub-Objectives:

  • Application of data mining and machine learning techniques to create behavioral model based on data collected from SDN and 5G networks to detect attacks on Telecom environments
  • Deployement of built intelligent models into telemetric point of presence to detect threats
  • Hooking security mitigation rules as a set of security functions chaining based on the output of intelligent detection models


  • State of the art in emerging network threats, enclosing cloud, 5G mobility and Internet of things
  • Application of data mining and machine learning techniques to detect threats
  • Use of detection models on specific security emerging network use-cases
  • Definition of all-in-one security approach, where mitigation is hooked based on the detection intelligence

Expertise and Skills Needed:

  • Good knowledge on networking security properties as well as traditional and newly-innovative cyber-threats
  • Preferably, good understanding of Emerging networking trends, Software Defined Network (SDN), automation, orchestration, Radio access networks
  • Sound understanding of data mining and machine learning techniques like diffrerent types of clustering, classification algorithms


For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects.
  2. Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!