Abstract
Some level of trust must be established before any collaboration
or interaction can take place. Since trust and privacy are closely intertwined, a mere possibility of a privacy violation reduces trust among interacting entities. This impedes sharing and dissemination of sensitive data. Affected interactions
range from simple transactions to the most complex collaborations.
We want to assist users in properly protecting their privacy in such interactions. We also wish to help users give up the minimum degree of privacy necessary to gain the required
level of trust—the level demanded by user’s partner as a pre-condition for a collaboration. In this paper, we focus on mechanisms for privacy-preserving dissemination of sensitive data. We next consider briefly the issues of privacy metrics
and trading privacy for trust. Our test application in the area of location-based routing and services illustrates how to use the proposed privacy-for-trust approaches.
Note
n Proceedings of NSF/NSA/AFRL Conference on Secure Knowledge Management (SKM), Amherst, N.Y.- Invited Paper
