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The design of smart electric grids and buildings that automatically optimize their energy generation and consumption is critical to advancing important societal goals, including increasing energy-efficiency, improving the grid's reliability, and gaining energy independence. To enable such optimizations, smart grids and buildings increasingly rely on Internet-connected sensors in smart devices, including digital electric meters, web-enabled appliances and lighting, programmable outlets and switches, and intelligent HVAC systems. However, a key barrier to the broad adoption of energy-related optimizations is that prior work has shown that Internet-connected sensors inadvertently leak sensitive private information about user behavior. For example, a high or variable home energy usage typically correlates with a home being occupied. To address the problem, this research will design low-cost, non-intrusive, privacy-enhancing techniques that reduce the sensitive information leaked through smart sensor-driven devices, while still permitting the sophisticated analytics, control, and verification necessary to enable energy optimizations for smart grids and buildings.
The research includes developing both consumer- and utility-driven mechanisms to preserve sensor-data privacy. The consumer-driven mechanisms leverage batteries, elastic appliances, noise injection, and renewable energy sources to obfuscate private information in externally visible energy usage data at low cost. The utility-driven mechanisms leverage cryptographic techniques within the devices themselves to enable utilities to implement critical electric grid optimizations, such as demand response, time-of-use billing, and fault localization, without requiring consumers to provide utilities, or other third-parties, with their raw sensor data. The research also develops an approach to controllable privacy, which enables users to control the amount of information smart devices leak to third parties. In this case, consumers voluntarily use smart devices, which are able to verify that consumers engage in some particular energy-efficient behavior without directly revealing sensitive information. The research includes implementing and evaluating the techniques in a prototype programmable building, which includes programmable smart devices, batteries, and renewable energy sources. The research and prototype provide awareness of smart grid privacy and its implications on public policy, and contribute to both graduate courses on smart grids and energy, as well as undergraduate research projects.
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Breakthrough: Enhancing Privacy in Smart Buildings and Homes