In the previous post we looked at a simple randomization procedure to obscure individual responses to yes/no questions in a way that retains the statistical usefulness of the data. In this post we’ll generalize that procedure, quantify the privacy loss, and discuss the utility/privacy trade-off. More general randomized response Suppose we have a binary response […]
Suppose you want to gather data on an incriminating question. For example, maybe a statistics professor would like to know how many students cheated on a test. Being a statistician, the professor has a clever way to find out what he wants to know while giving each student deniability. Randomized response Each student is asked […]
One problem with the nothing-to-hide argument is that it assumes innocent people will be exonerated certainly and effortlessly. That is, it assumes that there are no errors, or if there are, they are resolved quickly and easily. Suppose the probability of a correctly analyzing an email or phone call is not 100% but 99.99%. In […]
‘Big Data’ event now available to viewJuly 10, 2012 News No comments Print PDFThe Big Data Opportunity event, chaired last week (3 July 2012) by RSS executive director Hetan Shah and featuring cabin...
As this world gets more connected, and as data storage and analysis advances, we have to change our notions of privacy and data stewardship. About 25 years ago, right before email hit the big time and data analysis methods were limited to small dataset...
