Towards global Consensus on Trust

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Placeholder issue for master thesis work. End date firm: 16:00, Friday 31 August 2018, Cum Laude potential. Concrete idea:

• We aim to build a global consensus system for trust
• a required intermediary step is obtaining lists of trust rankings
• Each participant in the network puts periodically the Top-1000 nodes it trusts the most on their Trustchain.
• A signed trustranking record contains a list of known public keys of nodes, ordered by level of trust. Nodes with highest level of successful interaction and trust are listed first.
• Calculate Trustrankings using incremental personalised temporal pagerank #2805
• Extend trustchain on top of IPv8 #3272 to parse and interprete these records
• Calculate from numerous individual signed Trustranking records an estimation of the global trust consensus. Consensus Ranking
• Who is the most trusted of us all? In future work we can then run a Byzantine Fault Tollerant Consensus algorithm for true global consensus on trustranking. NP-Hard problem:

We are given a set of N rankings, or permutations1
on n objects. These rankings might represent individual
preferences of a panel of N judges, each presented
with the same set of n candidates. Alternatively, they
may represent the ranking votes of a population of N
voters. The problem of rank aggregation, or of finding
a consensus ranking, is to find a single ranking π0 that
best “agrees” with all the N rankings. This process
can also be seen as a voting rule, where the N voters’
preferences are aggregated in an election to produce
a consensus order over the candidates, the top ranked
being the winner.

• This enables random appointment of a node for some governance role, weighted by your global trust ranking. A fascinating mix of a meritocracy and democratic lottery. All based on the transaction graph and emergent trust network: