Principles of artificial intelligence
Principles of artificial intelligence
Agents, trust, and information access on the semantic web
ACM SIGMOD Record
Information Flow in a Purpose-Oriented Access Control Model
ICPADS '97 Proceedings of the 1997 International Conference on Parallel and Distributed Systems
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Privacy Promises, Access Control, and Privacy Management
ISEC '02 Proceedings of the Third International Symposium on Electronic Commerce
Decentralized Trust Management
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
Tropos: An Agent-Oriented Software Development Methodology
Autonomous Agents and Multi-Agent Systems
Trust-X: A Peer-to-Peer Framework for Trust Establishment
IEEE Transactions on Knowledge and Data Engineering
Purpose based access control of complex data for privacy protection
Proceedings of the tenth ACM symposium on Access control models and technologies
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Modeling Security Requirements Through Ownership, Permission and Delegation
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Platform for enterprise privacy practices: privacy-enabled management of customer data
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
Protecting privacy during on-line trust negotiation
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
Privacy is linking permission to purpose
SP'04 Proceedings of the 12th international conference on Security Protocols
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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.