Attributive concept descriptions with complements
Artificial Intelligence
Reasoning in description logics
Principles of knowledge representation
E-P3P privacy policies and privacy authorization
Proceedings of the 2002 ACM workshop on Privacy in the Electronic Society
Reasoning with Expressive Description Logics: Theory and Practice
CADE-18 Proceedings of the 18th International Conference on Automated Deduction
Proceedings of the 2002 workshop on New security paradigms
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Specifying privacy policies with P3P and EPAL: lessons learned
Proceedings of the 2004 ACM workshop on Privacy in the electronic society
SemWebDL: A privacy-preserving Semantic Web infrastructure for digital libraries
International Journal on Digital Libraries
WS-CatalogNet: an infrastructure for creating, peering, and querying e-catalog communities
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Web Services: Concepts, Architectures and Applications
Web Services: Concepts, Architectures and Applications
Formal consistency verification between BPEL process and privacy policy
Proceedings of the 2006 International Conference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services
A dynamic privacy model for web services
Computer Standards & Interfaces
Formalizing and reasoning with p3p policies using a semantic web ontology
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
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The emerging next generation Web technologies offer tremendous opportunities for automating information management in a variety of application domains including office tasks, travel, and digital government. One of the main challenges facing effective automation is privacy. Verifying the correct usage of collected personal data is a major concern for both individuals and organizations. In this paper, we present a framework for reasoning about privacy models including provider’s privacy policies and user’s privacy preferences. More specifically, we use a Description Logic (DL) based notation to specify privacy abstractions. We provide a formalization of matching user’s privacy preferences against provider’s privacy policies using DLs’ reasoning mechanisms. We have implemented a Privacy Match Engine(PME) which is based on RACER.