Recommendation Privacy Protection in Trust-based Knowledge Sharing Network
W. Guo, und S. Kraines. Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Korea, (November 2007)
Zusammenfassung
Trust can be applied to knowledge sharing on a distributed network of knowledge source agents. Each agent represents a person who trusts some other agents. Based on these trust-relationships, an agent can infer the trustworthiness of an unknown agent by asking trusted agents for recommendations. However, the person represented by an agent may not be willing to share his or her individual opinion about the trustwor-thiness of a particular agent to agents that do not protect information privacy. A solution for this issue is proposed using three kinds of privacy policies: generosity, caution, and non-cooperation. An agent that adopts the caution policy towards another agent will hide the details of the trust recommendation path. An analysis shows the effect of the privacy policies on the calculated reliabilities of the recommended trust values.
%0 Conference Paper
%1 Guo/2007/Recommendation
%A Guo, Weisen
%A Kraines, Steven
%B Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Korea
%D 2007
%E Finin, Tim
%E Kagal, Lalana
%E Olmedilla, Daniel
%K 2007 iswc knowledge network privacy protection recommendation sharing workshop_peas
%T Recommendation Privacy Protection in Trust-based Knowledge Sharing Network
%X Trust can be applied to knowledge sharing on a distributed network of knowledge source agents. Each agent represents a person who trusts some other agents. Based on these trust-relationships, an agent can infer the trustworthiness of an unknown agent by asking trusted agents for recommendations. However, the person represented by an agent may not be willing to share his or her individual opinion about the trustwor-thiness of a particular agent to agents that do not protect information privacy. A solution for this issue is proposed using three kinds of privacy policies: generosity, caution, and non-cooperation. An agent that adopts the caution policy towards another agent will hide the details of the trust recommendation path. An analysis shows the effect of the privacy policies on the calculated reliabilities of the recommended trust values.
@inproceedings{Guo/2007/Recommendation,
abstract = {Trust can be applied to knowledge sharing on a distributed network of knowledge source agents. Each agent represents a person who trusts some other agents. Based on these trust-relationships, an agent can infer the trustworthiness of an unknown agent by asking trusted agents for recommendations. However, the person represented by an agent may not be willing to share his or her individual opinion about the trustwor-thiness of a particular agent to agents that do not protect information privacy. A solution for this issue is proposed using three kinds of privacy policies: generosity, caution, and non-cooperation. An agent that adopts the caution policy towards another agent will hide the details of the trust recommendation path. An analysis shows the effect of the privacy policies on the calculated reliabilities of the recommended trust values.},
added-at = {2007-11-07T19:19:39.000+0100},
author = {Guo, Weisen and Kraines, Steven},
biburl = {https://www.bibsonomy.org/bibtex/26df042ed169a93ba1ff72437eb4d63c6/iswc2007},
booktitle = {Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Korea},
crossref = {http://data.semanticweb.org/workshop/peas/2007/proceedings},
editor = {Finin, Tim and Kagal, Lalana and Olmedilla, Daniel},
interhash = {b12f34f1bba2ecc3cb72d72356ccdb26},
intrahash = {6df042ed169a93ba1ff72437eb4d63c6},
keywords = {2007 iswc knowledge network privacy protection recommendation sharing workshop_peas},
month = {November},
timestamp = {2007-11-07T19:20:49.000+0100},
title = {Recommendation Privacy Protection in Trust-based Knowledge Sharing Network},
year = 2007
}