Ryerson researcher using smart analytics to protect smart meter data

Researcher: Dr. Andriy Miranskyy, Ryerson University
Project title: Smart Analytics for Smart Grid
Industry Partners: IBM Canada Ltd.
Supported by: SOSCIP, Federal Economic Development Agency for Southern Ontario, IBM Canada Ltd., Ryerson University’s Faculty of Science

Cybersecurity Energy

How we use energy reveals vital information about our everyday behaviour – from our work and school schedules to when we are likely to be sleeping, eating and performing simple chores such as laundry or washing dishes. It even reveals when we are on vacation.

While this information in the wrong hands could put us at risk, it also plays an important role in reducing our carbon footprint and ensuring the cost of energy is kept relatively low.

Power generation companies use information derived from microclimate, small areas within general climate zones, to accurately predict power generation needs. Microclimate information is captured from smart meters, which wirelessly transmits data from our homes to utility companies.

Considering that more than one million smart meters have been installed in Ontario homes since 2010 and that number continues to grow, it’s necessary to find a way to ensure the data captured by smart meters is protected and secure from threat.

A professor from Ryerson University’s Department of Computer Science, Andriy Miranskyy, and his team, are using SOSCIP’s computing platforms to help power generation companies capture the data they need to accurately make these predictions while also respecting consumers’ privacy.

The interdisciplinary team includes IBM Canada’s Dr. Biruk Habtemariam, Prof. Ali Miri from Ryerson University, Prof. Saeed Samet from Memorial University and Prof. Matt Davison from Western University. Their goal is to develop data aggregation and obfuscation techniques that will prevent privacy violation, yet yield the information needed for accurate prediction of power consumption.

“This will enable utility companies to open up data to external groups without jeopardizing the privacy of the millions of people they’re collecting data from,” explained Miranskyy.

The team is using the SOSCIP Cloud Data Analytics Platform to test the formula’s validity using simulated data. The Cloud platform, which is based at Western University, is being used to develop an algorithm which will allow them to predict electricity usage in near-real time by a third party while keeping the data captured by smart meters secure. Essentially, the secure linear regression algorithm allows researchers to compute numbers without actually being able to view those numbers.

The SOSCIP Cloud Data Analytics Platform is the first research-dedicated cloud-based analytics environment in Canada and is unique in that it provides access to a broad array of IBM software tools for application development and data analytics which can be combined with user-specific and other open source software to create customized virtual machines to meet project demands.

“The goal is to make Ontario a leader in this fast growing technology area,” said Miranskyy. “Allowing utility companies and other third parties to provide better services to Ontario residents, leading to energy conservation and reduced infrastructure costs.”

The team’s work, Privacy Preserving Predictive Analytics with Smart Meters, has been published to appear in the Proceedings of the 5th IEEE International Congress on Big Data, 2016.


SOSCIP is a research and development consortium that pairs academic and industry researchers with advanced computing tools to fuel Canadian innovation. SOSCIP supports projects that have the potential to have a considerable impact on the lives of Canadians, within areas such as water, cities, health and cybersecurity. The consortium includes 15 of Ontario’s most research-intensive academic institutions as well as Ontario Centres of Excellence and the IBM Canada Research and Development Centre.