Big Data Cybersecurity Threat Management and Visualization- ON-461

Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: Calian Ltd
Project Length: 6 months to 1 year
Preferred start date: 06/01/2021
Language requirement: English
Location(s): Ottawa, ON, Canada; Canada
No. of positions: 3-5
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About the company: 

Calian is a highly diversified Canadian company that delivery health, engineering, learning, advanced technology, and IT and cyber security solutions for our clients. The IT services and cyber security domains are major growth areas for defence, security, government, and private sector clients. Cyber security impacts virtually all organizations in some way; continuity of IT service and security of data is important for all businesses. We are prioritizing growth of our IT and cyber security business unit, and this means investing in research and development to bring the newest and most current solutions to our clients. 

Please describe the project.: 

This project is about researching how we can improve visualization of big data related to cybersecurity threat detection and prevention. Existing tools provide some visualization, though there are limits to what exisitng tools can provide. This project will research the limits of the applications for visualization of exisiting big data analytics and open source tools in sourcing, categorizing, and handling cybersecurity threats.

Investigation will focus on 3 main research questions:

Intelligent Risk management

What are the limits of the existing tools, systems, and approaches for sourcing, categorizing, and handling security threats without delay?

Threat visualization:

What are the limits of the existing for existing tools, systems, and approaches for  using current and historical data to establish statistical understanding of which threats are manageable and which pose unacceptable risk?

Predictive models:

What is the degree of confidence in the existing predictive models and tools for automatically issuing alerts when entry point for a cybersecurity attack is detected  compared to human-only-detection? Machine learning and artificial intelligence may play role in developing such a mechanism.

The main goal is identifying the level of current performance with existing tools and determine the level of effort required to development an improved threat management and visualization prototype.
Propose metrics / KPIs to measure the effectiveness of the threat management visualization prototype with real-world data.

Main tasks to be performed by the candidate:

  • Develop perfomance meaurement frameworks for existing tools, systems and approaches
  • Perfomance measurement for existing tools, systems and approaches using sample threats.
  • Identify limitations and propose new technqiues to improve performance
  • Full-stack development

Methodology/techniques to be used:

  • Attack trees and data flow mapping
  • Agile and Continuous Integration/ Continuous Delivery

Required expertise/skills: 

  • UI/UX – HTML5, CSS3, JS, JQuery, Vu/Angular/React, Graph libraries (D3/GoogleCharts/ChartJS)
  • Middleware – REST APIs, Node.js Ecosystem/Java Ecosystem/Spring Ecosystem
  • Backend – MySQL/PostgreSQL/SQLServer
  • Experience with reports
  • Experience with APIs
  • Experience with a variety of open source code
  • Experience with Agile development and CI/CD, Git
  • Experience with Linux, nice to have - Bash/Shell
  • Nice to have – Elasticsearch experience