White House references Wicker, Thomas work in new report on big data and privacy

After 90 days of scrutinizing how big data will inevitably transform the way we live and work as well as alter the relationships between government, citizens, businesses, and consumers, the White House issued its Big Data Working Group report on May 1, 2014.


After 90 days of scrutinizing how big data will inevitably transform the way we live and work as well as alter the relationships between government, citizens, businesses, and consumers, the White House issued its Big Data Working Group report on May 1, 2014.

“Big Data: Seizing Opportunities, Preserving Values,” focuses on how the public and private sectors can maximize the benefits of big data while minimizing its risks. It also identifies opportunities for big data to grow our economy, improve health and education, and make our nation safer and more energy efficient. 1

Probing issues of big data and privacy, the report references a paper authored by ECE Professor Stephen Wicker and ECE Professor Emeritus Robert Thomas, “Privacy-Aware Architecture for Demand Response Systems,” published in 2011 for the 44th Hawaii International Conference on System Sciences. 2

According to the report, big data technologies, together with the sensors that ride on the “Internet of Things,” pierce many spaces that were previously private. Signals from home WiFi networks reveal how many people are in a room and where they are seated. Power consumption data collected from demand-response systems show when you move about your house.

In their article, Wicker and Thomas analyze the privacy issues implicated by the development of demand response systems, highlighting the invasive nature of fine-granularity power consumption data. They show that the data collected by Advanced Metering Infrastructure (AMI) reveals detailed information about a person’s behavior within their home. Additionally, they demonstrate how privacy-aware design principles lead to novel system architectures that realize the benefits of demand response without requiring that AMI data be centrally collected. The resulting systems avoid both harm to subscribers and the potential need to scrap AMI-based demand response efforts in the face of public outcry. They also show that Trusted Platform Modules can be used to develop privacy-sensitive metering infrastructure.

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