Distributed Trust Algorithms: Difference between revisions

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<th>Concatenation of x&nbsp;->&nbsp;y</th>
<th>Concatenation of x&nbsp;->&nbsp;y</th>
<th>Multiple paths</th>
<th>Multiple paths</th>
<th>Concat associative?</th>
<th>notes</th>
<th>notes</th>
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<td>(x*y)<sup>&frac12;</sup></td>
<td>(x*y)<sup>&frac12;</sup></td>
<td>maximum</td>
<td>maximum</td>
<td>Y</td>
<td></td>
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<td>[http://www.trustlet.org/wiki/MoleTrust MoleTrust]</td>
<td>N</td>
<td>[0,1]</td>
<td>(x*y)</td>
<td>weighted</td>
<td>avoid cycles, a couple cutoff thresholds</td>
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<td>[http://www.advogato.org/trust-metric.html Advogato]</td>
<td>[http://www.advogato.org/trust-metric.html Advogato]</td>
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<td>Y, starting to</td>
<td>Y, starting to</td>
<td>bilattice</td>
<td>bilattice</td>
<td></td>
<td></td>
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<td>N</td>
<td>N</td>
<td>untrusted, marginal, full, ultimate</td>
<td>untrusted, marginal, full, ultimate</td>
<td></td>
<td></td>
<td></td>
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<td></td>
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<td>1-(1-y)<sup>x</sup></td>
<td>1-(1-y)<sup>x</sup></td>
<td>average</td>
<td>average</td>
<td>Y</td>
<td>trust values intertwined with # of "good" or "bad" experiences with an entity. Pay attention to "recommendation trust"</td>
<td>trust values intertwined with # of "good" or "bad" experiences with an entity. Pay attention to "recommendation trust"</td>
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<td>[http://en.wikipedia.org/wiki/EigenTrust EigenTrust]</td>
<td>[http://en.wikipedia.org/wiki/EigenTrust EigenTrust]</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>

Revision as of 18:29, 23 June 2008

Between people

Name Based on psych. research? Data model Concatenation of x -> y Multiple paths notes
Konfidi Multiplicative2 N [0,1] (x*y)½ maximum
TidalTrust N 1-10
MoleTrust N [0,1] (x*y) weighted avoid cycles, a couple cutoff thresholds
Advogato Uses Network Flow theory; has central root nodes
Patricia Victor's Y, starting to bilattice
OpenPGP N untrusted, marginal, full, ultimate


Between agents

Reputation is generally part of the algorithm

Valuation of Trust in Open Networks

Beth, Borcherding, Klein 1994

N [0,1) 1-(1-y)x average trust values intertwined with # of "good" or "bad" experiences with an entity. Pay attention to "recommendation trust"
EigenTrust