Mitacs Postdoc Internship (Ericsson; St. Laurent, QC) – Security Intelligence in Emerging Networks
Desired Start Date: ASAP
Mitacs Program: Accelerate
Project Length: 2 years
Location: St. Laurent, QC
No. of Positions Available: 1
Language: English / Bilingual
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).
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:
- Democratization of software defined hybrid (wired and wireless) wide area networks
- Automation and orchestration, where artifacts like Docker and Kubernetes allow to provision networking elements
- Private and public cloud connectivity, where companies want to shift workloads from public cloud to private data-centers
- 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, the Research Area will be devoted on the following themes:
- Study of threats landscape in emerging networks
- Leveraging collected data to create an intelligence model to detect malicious activities in emrging networks
- Adapt the threats’ detection to emerging networks
The candidate should be curious, ready to learn, and passionate in the following areas:
- Emerging networks (e.g., mobility/5G)
- Content delivery networks
- Edge computing
- 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 passionate about doing research in an industrial environment.
Candidates with the academic or industrial background who have the ability to realize prototypes and publish scientific papers, are encouraged.
The candidate should also be autonomous to a certain degree and ready to deliver results as needed, though it is understood that there will be a learning curve to align with Ericsson.
For more info or to apply to this applied research position:
|Eligibility Requirements:||PhD in Computer Engineering.|
|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
|Research 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 telemtric 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
|Methodology:||1. State of the art in emerging network threats, enclosing cloud, 5G mobility and Internet of things
2. Application of data mining and machine learning techniques to detect threats
3. Use of detection models on specific security emerging network use-cases
4. Definition of all-in-one security approach, where mitigation is hooked based on the detection intelligence