  The problem of private information "leakage" (inadvertently or by malicious
design) from the myriad large centralized searchable data repositories drives
the need for an analytical framework that quantifies unequivocally how safe
private data can be (privacy) while still providing useful benefit (utility) to
multiple legitimate information consumers. Rate distortion theory is shown to
be a natural choice to develop such a framework which includes the following:
modeling of data sources, developing application independent utility and
privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type
of data sources or the methods of providing privacy, developing a
side-information model for dealing with questions of external knowledge, and
studying a successive disclosure problem for multiple query data sources.
