Abstract

Today, many online companies are gathering information and assembling sophisticated databases that know a great deal of information about many people, generally without the knowledge of those people. Such endeavor has resulted in the unprecedented attrition of individual’s right to informational self-determination. On the one hand, Consumers are powerless to prevent the unauthorized dissemination of their personal information, and on the other, they are excluded from its profitable commercial exchange. This paper focuses on developing knowledge-empowered agent information system for privacy payoff as a means of rewarding consumers for sharing their personal information with online businesses. The design of this system is driven by the following argument: if consumers’ personal information is a valuable asset, should they not be entitled to benefit from their asset as well? The proposed information system is a multi-agent system where several agents employ various knowledge and requirements for personal information valuation and interaction capabilities that most users cannot do on their own. The agents in the information system bear the responsibility of working on behalf of consumers to categorize their personal data objects, report to consumers on online businesses’ trust 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. The details of the system as well as a proof-of-concept implementation using JADE (Java Agent Development Environment) are presented here.

@article {springerlink:10.1007/s10115-011-0415-3,
   author = {Yassine, Abdulsalam and Nazari Shirehjini, Ali A. and Shirmohammadi, Shervin and Tran, Thomas},
   affiliation = {Distributed and Collaborative Virtual Environments Research Laboratory, School of Information Technology and Engineering SITE, University of Ottawa, Ottawa, ON, Canada},
   title = {Knowledge-empowered agent information system for privacy payoff in eCommerce},
   journal = {Knowledge and Information Systems},
   publisher = {Springer London},
   issn = {0219-1377},
   keyword = {Computer Science},
   pages = {1-29},
   url = {http://dx.doi.org/10.1007/s10115-011-0415-3},
   note = {10.1007/s10115-011-0415-3},
   year = {2011}
}