Evaluation of ML-based Intrusion Detection algorithms

This research will determine which combinations of metrics sets and machine learning algorithms
provide the most accurate outcomes when analyzing the data produced in the CSE-IDC-IDS2018 dataset.

Faculty Supervisor:

Jonathan Anderson

Student:

Partner:

NASDAQ Canada Inc

Discipline:

Computer science

Sector:

Information and Communications Technology; Health and Related Sciences & Technology; Finance and Insurance

University:

Memorial University of Newfoundland

Program:

Accelerate

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