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Novel Machine Learning Visualization of Threat Analysis for Cybersecurity Operations
This project will combine graduate level research expertise with best-in-class managed detection and response security operations, to develop ‘collaborative intelligence’ oriented tooling, in order to support Security Operations Centre (SOC) personnel in rapidly assessing the threat potential of suspect command lines and similar text objects. From a recent analysis of SOC AI usage, it is evident that rapid threat analysis of obfuscated or otherwise complicated code objects is a prime opportunity to enhance SOC performance. We will leverage modern ML, AI, and visualization tools to develop innovative and highly functional SOC threat analysis tooling.
Faculty Supervisor:
Jian Zhao
Student:
Partner:
eSentire
Discipline:
Computer science
Sector:
Information and cultural industries; Professional, scientific and technical services
University:
University of Waterloo
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.