In the information realm, loss of privacy is usually associated with failure to control access to information, to control the flow of... » More

In the information realm, loss of privacy

is usually

associated with failure to control

access to

information, to control the flow of information, or

to control the purposes for which information

is

employed. Differential privacy arose in a context

in which ensuring privacy is a challenge even if all

these control problems are solved: privacy-preserving

statistical analysis of data.

The problem of statistical disclosure control—

revealing accurate statistics about a set of respondents

while preserving the privacy of individuals—has

a venerable history, with an extensive literature

spanning statistics, theoretical computer science,

security, databases, and cryptography (see,

for example, the excellent survey of Adam and

Wortmann,1 the discussion of related work in Blum et

al.,2 and the Journal of Official Statistics dedicated to

confidentiality

and disclosure control).

« Hide