Differential privacy for distributed computing
Information targeting and delivery is a crucial requirement
for current applications and services both on the fixed Internet
and the mobile Internet. The content delivery mechanism
needs to take user privacy into account in order to prevent
information leakage and possible privacy problems.
Issues pertaining to the privacy of a data set have been
investigated in the work on k-anonymity for data sets.
More recently, differential privacy has been proposed
for ensuring privacy by adding noise to a statistical
database. This thesis work investigates the application
of the k-anonymity concept and differential privacy
for distributed systems.