Smart Grid Project

Data Privacy

Data Privacy for Smart Meters and Smart Devices: A Scenario-Based Study


Principal investigator: Jason Dedrick, Co-PI: Jeffrey Stanton, Syracuse University Contact: jdedrick@syr.edu

Smart meters capture data on household energy usage which can be used by utilities to automate meter reading and billing, detect and respond to outages, manage grid operations, and better match supply to demand. In addition a new generation of smart home products is being introduced to the market, such as smart thermostats, lighting systems, and devices that can help customers manage energy use. These technologies offer potential value to consumers, but may also raise privacy concerns for some consumers. They may worry about what data is being collected, who has access to the data, and how it might be used.

This project investigates the privacy attitudes, concerns, and practices of consumers, device manufacturers, policymakers and regulators. The goal is to provide fact-based analysis that will help develop solutions that give customers confidence about the protection of their privacy and allow data to be used in ways that benefit consumers and firms.

The project uses focus groups, interviews and a survey to addresses the following research questions:

1. How do consumers perceive privacy risks when presented with information about the nature of data collection and use by utilities and others?

2. How do utility companies and other firms currently protect data privacy and how well do their policies and practices correspond to the privacy concerns of consumers?

3. Given information about consumers’ concerns, what privacy policies and practices will utility companies, other firms and regulators recommend as appropriate, and how will consumer concerns be addressed?

The project will advance knowledge in the field of privacy in information systems; and will provide insights to utilities, policy makers, regulators, privacy advocates, consumers and other stakeholders.

Acknowledgement: This research is supported by a grant from the U.S. National Science Foundation (SES-1447589), and a grant from the Alfred P. Sloan Foundation. .

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