  With the rapid development of applications in open distributed environments
such as eCommerce, privacy of information is becoming a critical issue. Today,
many online companies are gathering information and have assembled
sophisticated databases that know a great deal about many people, generally
without the knowledge of those people. Such information changes hands or
ownership as a normal part of eCommerce transactions, or through strategic
decisions that often includes the sale of users' information to other firms.
The key commercial value of users' personal information derives from the
ability of firms to identify consumers and charge them personalized prices for
goods and services they have previously used or may wish to use in the future.
A look at present-day practices reveals that consumers' profile data is now
considered as one of the most valuable assets owned by online businesses. In
this thesis, we argue the following: if consumers' private data is such a
valuable asset, should they not be entitled to commercially benefit from their
asset as well? The scope of this thesis is on developing architecture for
privacy payoff as a means of rewarding consumers for sharing their personal
information with online businesses. The architecture is a multi-agent system in
which several agents employ various requirements for personal information
valuation and interaction capabilities that most users cannot do on their own.
The agents in the system bear the responsibility of working on behalf of
consumers to categorize their personal data objects, report to consumers on
online businesses' trustworthiness and reputation, determine the value of their
compensation using risk-based financial models, and, finally, negotiate for a
payoff value in return for the dissemination of users' information.
