Grants and Contributions:

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Title:

Robust and Resilient Machine Learning for Connected Health-Care Systems

Agreement Number:

984858

Agreement Value:

$300,564.00

Agreement Date:

Sep 9, 2022 - Aug 31, 2025

Description:

The Project focuses on building resilient and secure machine learning (ML) techniques for connected health-care systems. With the advent of connected medical devices, there is immense potential for continuous onsite data gathering and analysis. Recent advances in ML techniques have unlocked significant potential for automated detection and diagnosis of medical conditions and disease monitoring, especially for remote and vulnerable populations. Unfortunately, this has also opened the doors to many kinds of malicious security attacks, especially those targeting the ML algorithms via adversarial attacks (i.e., evasion and poisoning attacks). The Project will investigate systematic techniques for making ML algorithms used in the healthcare domain robust and resilient to different kinds of attacks, and to provide early warning of attacks on the medical devices so that suitable actions can be taken. The team will leverage its collective expertise in the domains of cyber-security, dependability, and machine learning, to develop fundamental innovations in this area.

Organization:

National Research Council Canada

Expected Results:

In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.

Location:

Vancouver, British Columbia, CA V6T 1Z3

Reference Number:

172-2021-2022-Q3-984858

Agreement Type:

Grant

Report Type:

Grants and Contributions

Recipient Business Number:

108161779

Recipient Type:

Academia

Recipient's Legal Name:

The University of British Columbia

Federal Riding Name:

Vancouver Quadra

Federal Riding Number:

59039

Program:

Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Program Purpose:

Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.

NAICS Code:

541710