Presentation at the "Weaving Relations of Trust in Crowd Work: Transparency and Reputation across Platforms" workshop @ WebSci16

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Provenance as a Key Factor for
Privacy-proof Trust
Davide Ceolin

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• Cold-start Problem.
We need observations to build user reputations.
• Privacy Intrusion.
Knowledge about individuals reduces uncertainty.
• Inaccurate Point-wise Prediction.
Reputations are asymptotically correct.
Open Issues

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• Reputation systems are (mostly) user-centric.
• Besides the who we can use also the when, where and how
provenance.
Provenance for Trust Estimation
waisda.nl

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• Provenance traces are fine-grained representations of how data came
to be.
• To derive trust estimations we need to identify links and regularities.
• We proposed to use provenance stereotypes:
• Clusters of provenance traces representing user behaviours
(e.g., early-morning weekend contributors).
Provenance for Trust Estimation

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• By aggregating traces, we can increase the availability of reputations:
• Users might be unknown, but their behaviour could be well-known.
• This helps mitigating uncertainty.
Provenance vs. cold-start

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• Users tend to adopt uniform behaviours.
• We can focus on the provenance stereotype (and hence on the cluster
of users) rather than on individuals.
• This adds an obfuscation layer.
Provenance vs. privacy intrusion

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• Probabilistic reputations are asymptotically accurate.
• Combining individual reputations with stereotypes:
• improves accuracy;
• allows discriminating among user contributions.
Provenance for point-wise predictions

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www.amsterdamdatascience.nlProvenance as a Key Factor for Privacy-proof Trust
• We adopted provenance stereotypes in a few Cultural Heritage case
studies.
• The creation of stereotypes needs to be standardised in order to
balance:
• performance (accuracy and efficiency);
• evidence availability;
• privacy.
Conclusion

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Thanks
d.ceolin@vu.nl