Privacy and Background Knowledge

author: Johannes Gehrke, Cornell University
published: Feb. 25, 2007,   recorded: August 2005,   views: 3903

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

The digitization of our daily lives has led to an explosion in the collection of data by governments, corporations, and individuals. Protection of confidentiality of this data is of utmost importance. However, knowledge of statistical properties of private data can have significant societal benefit, for example, in decisions about the allocation of public funds based on Census data, or in the analysis of medical data from different hospitals to understand the interaction of drugs. I will start by introducing two application scenarios, privacy-preserving data analysis and privacy-preserving data publishing. I will show how in simple models background knowledge can lead to severe breaches of privacy in both applications, and I will describe how proper modeling of background knowledge can avoid privacy breaches. I will outline first algorithmic steps towards privacy-preserving data analysis and data publishing with background knowledge, and I will conclude with open problems.

See Also:

Download slides icon Download slides: icml05_gehrke_pbk_01.pdf (731.7┬áKB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: