Revealing information while preserving privacy (Dinur & Nissim, 2002)
We examine the tradeoff between privacy and usability of statistical databases. Our main result is a polynomial reconstruction algorithm of… read more
We examine the tradeoff between privacy and usability of statistical databases. Our main result is a polynomial reconstruction algorithm of… read more
Differential privacy is a rigorous mathematical definition of privacy. In the simplest setting, consider an algorithm that analyzes a dataset… read more
Detractors often depict privacy work as being “ideological.” If believing that people shouldn’t live in fear of their tech betraying… read more
Tech companies have repeatedly reassured the public that trackers used to follow smartphone users through apps are anonymous or at… read more
While one data broker might only be able to tie my shopping behavior to something like my IP address, and… read more
As Information & Privacy Commissioner for Ontario, Canada, Dr. Ann Cavoukian developed the Privacy by Design (PbD) framework. Privacy by… read more
Public polling data from Pew Research reveals that American adults are more concerned about corporate data collection, tracking, and privacy… read more
Information about you, what you buy, where you go, even where you look is the oil that fuels the digital… read more
Bode, K. (2019, February 3). Researchers find ‘anonymized’ data is even less anonymous than we thought. Vice. https://www.vice.com/en_us/article/dygy8k/researchers-find-anonymized-data-is-even-less-anonymous-than-we-thought
This series from the Electronic Frontier Foundation pulls back the curtain on corporate personal data tracking, the use of online… read more