Professor Florian Kerschbaum has been awarded $2 million through the Ontario Research Fund to develop innovative data science and machine learning techniques aimed at safeguarding Ontario’s financial technology and manufacturing sectors from inadvertent data leaks. The project, led by Professor Kerschbaum as principal investigator and Professor N. Asokan as co-principal investigator, will enhance data security in these critical industries.
“By investing in cutting-edge research, we are safeguarding Ontario’s position at the forefront of innovation that continues to be competitive on a global scale and has the ability to attract the best and brightest talent to our province,” said Jill Dunlop, Minister of Colleges and Universities. “This will help ensure the social and economic opportunities that result from discoveries made in Ontario benefit Ontarians and the Ontario economy.”
ORF contributes up to one-third of the total project funding, with the remaining funds provided by private sector and institutional partners. Professor Kerschbaum’s research is one of four ORF-supported projects, totaling nearly $8 million, allocated to Waterloo researchers.
This project is supported by ORF as well as support from RBC, Intel, and the National Research Council Canada. The proposal and research are supported by the Cybersecurity and Privacy Institute and the Math Faculty's Innovation Office.
“At RBC, we value the privacy and security of our clients above all and throughout the years, we’ve had the opportunity to develop and help support initiatives that enhance and innovate on what’s possible in these critical areas of cyber safety,” said Eddy Ortiz, VP, Solution Acceleration & Innovation at RBC (inset on right). “As a result, we’ve been able to successfully launch numerous privacy-preserving patents, publications and products, including our virtual clean room, Arxis. We are also proud to work and collaborate with some of the leading laboratories in the world, including University of Waterloo, in the area of federated learning.”
L to R: Professors Florian Kerschbaum and N. Asokan
Professor Kerschbaum is recognized internationally for his expertise in data security. In 2019, he was named the NSERC/RBC Industrial Research Chair in Data Security, the same year he became an ACM Distinguished Member as well as recognized by CS-Can | Info-Can as an Outstanding Young Computer Scientist. In 2020, he became a Fellow of the Balsillie School of International Affairs and in 2022 received the Faculty of Mathematics Golden Jubilee Research Excellence Award.
Professor Asokan joined the Cheriton School of Computer Science in September 2019 as a Cheriton Chair, an endowed position supported by the David R. Cheriton Endowment for Excellence in Computer Science. He is a principal investigator at the Private AI Collaborative Research Institute, a research group funded jointly by Intel Labs and other industry partners to develop fundamental technologies that are instrumental in strengthening the security, privacy and trustworthiness of decentralized artificial intelligence. In 2018, he was named a Fellow of ACM and, in 2023, a Fellow of the Royal Society of Canada. He is also the Director of the Cybersecurity and Privacy Institute.
About the research
Professor Kerschbaum’s research will address the growing demand for data collection in the digital economy while ensuring robust data privacy protections. Protecting data privacy is essential to prevent accidental leaks of private information. Although data science involves intentionally releasing some information, privacy-preserving techniques — such as those provided by cryptography and statistical guarantees — can limit what can be inferred about private data. As such, systems designed for privacy-preserving data science must balance intentional leakage against the risk of unintentional leakage, while being computationally efficient.
“Our project aims to address this trade-off in utility, privacy and efficiency in private computation by taking a holistic approach to data science,” said Professor Kerschbaum. “The goal is to achieve better trade-offs that benefit Ontario’s fintech and manufacturing industries by supporting their business goals while preserving privacy for both their customers and businesses. As the project has many components, it will also result in training dozens of students at both undergraduate and graduate levels over five years, providing them with the knowledge and expertise for careers in privacy-preserving data science.”
