Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

Network intrusion detection is a complex and evolving challenge with the increasing size and complexity of modern computerx000D
networks and the vast quantity of data they generate. Processing this vast amount of information in today's networks is beyondx000D
human capabilities and necessitates automated filtering mechanisms that identify potential intrusions for human operatorx000D
investigation. To address this issue, Rank, Inc. will partner with the University of Toronto to develop novel anomaly detectionx000D
systems - filtering mechanism that ingest normal activity in the network and then monitor for suspicious threats over time. Thesex000D
novel methods are based on machine learning principles that will not only provide improved detection rate, but also supply humanx000D
operators with explanations for identified anomalies in order to assist their decision-making process.x000D
Rank, Inc. develops solutions for monitoring network traffic to detect possible network intrusions. The proposed project seeks tox000D
improve the toolkit developed by Rank, Inc. by advancing their anomaly detection suite with advanced concepts of deep learning.x000D
The proposed innovations are crucial for Rank, Inc. as they compete with other solution providers in the cybersecurity space andx000D
will enable a development of a unique solution which will benefit the company from direct sales.