Privacy becomes a major concern for both customers and enterprises
in today’s corporate marketing strategies, many research efforts
have been put into developing new privacy-aware technologies. Among
them, Hippocratic databases are one of the important mechanisms to
guarantee the respect of privacy principles in data management, which
adopt purpose as a central concept associated with each piece of data
stored in the databases. The proposed mechanism provides basic principles
for future database systems protecting privacy of data as a founding
tenet. However, Hippocratic databases do not allow to distinguish which
particular method is used for fulfilling a purpose. Especially, the issues
like purpose hierarchies, task delegations and minimal privacy cost are
missing from the proposed mechanism.
In this paper, we extend these mechanisms in order to support
inter-organizational business processes in Hippocratic databases. A comprehensive
approach for negotiation of personal information between
customers and enterprises based on user preferences is developed when
enterprises offer their clients a number of ways to fulfill a service. We
organize purposes into purpose directed graphs through AND/OR decomposition,
which supports task delegations and distributed authorizations.
Specially, customers have controls of deciding how to get a service
fulfilled on the basis of their personal feeling of trust for any service customization.
Quantitative analysis is performed to characterize privacy
penalties dealing with privacy cost and customer’s trust. Finally, efficient
algorithms are given to guarantee the minimal privacy cost and
maximal customer’s trust involved in a business process.