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@ -7,14 +7,14 @@ category: Informational
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tags: logos/reputation
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editor: Mark Evenson <mark.evenson@status.im>
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contributors:
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- Alvaro
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- Álvaro Castro-Castilla
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---
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# Abstract
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We present Ininkgut, a deceptively simple algorithm for computing the
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reputation of other nodes in their performance of a shared alogrithm.
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We present Ikingut: an algorithm for purely local computation of peer
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node reputation based on their observed performance of a shared
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computation.
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# Background
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@ -33,10 +33,13 @@ node reputation is to
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- Providing a mechanism for bootstrapping networks, with a low
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number of nodes.
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# Theory / Semantics
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# Theory
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## Ikingut Algorithm
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A deceptively simple algorithm for computing reputation of a other
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network nodes based on observed past performance.
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### Concept
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The Ikingut algorithm for reputation is a local heuristic computed
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@ -56,9 +59,9 @@ Other relevant characteristics of the algorithm are:
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functions.
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- Lightweight. It doesn’t perform long computations nor use a lot of
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memory.
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- Pluggable into Glacier and Snowball. It’s designed to fit well with
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swarm-like consensus algorithms. Moreover, it augments the consensus
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algorithm without altering it.
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- Pluggable into Glacier and Snowball [38/LOGOS-CONSENSUS][]. It’s
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designed to fit well with swarm-like consensus algorithms. Moreover,
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it augments the consensus algorithm without altering it.
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- Adaptive. It processes network and behavior changes fast.
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- Dynamic. It introduces new nodes consistently and fairly.
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- It is robust against strategic adversaries. We will see these in more detail below.
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@ -84,14 +87,13 @@ of the consensus algorithm.
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operation.
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3. If the resulting reputation is negative, add it to the trust
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score, using the following equation:
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$$
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t_i := min(at_i, t_i + br_i) \\
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\text{where}\ 0 < a < 1 \ \text{and} \ b > 1 \\
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$$
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where $a$ and $b$ are constants used to manipulate how much
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momentum is applied.
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$$
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t_i := min(at_i, t_i + br_i)\\
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\text{where}\ 0 < a < 1 \ \text{and} \ b > 1
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$$
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Where $a$ and $b$ are constants used to manipulate how much
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momentum is applied.
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**Pseudocode:**
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@ -145,8 +147,19 @@ from these two operations:
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- Bring the opportunity of building reputation faster.
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- Ensure accumulation of negative scores for misbehaving nodes.
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# Security/Privacy Considerations
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# Implementation status
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Incomplete. No publically known implementations.
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# Sovereignty Considerations
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## Privacy
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Computation of reputation is purely local from observed behavior.
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## Security
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No model constructed. No current tests.
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# Copyright
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@ -157,5 +170,7 @@ Copyright and related rights waived via
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## informative
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#. 38/LOGOS-CONSENSUS
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#. Rocket, Team, Maofan Yin, Kevin Sekniqi, Robbert van Renesse, and Emin Gün Sirer. “Scalable and Probabilistic Leaderless BFT Consensus through Metastability.” arXiv, August 24, 2020. https://doi.org/10.48550/arXiv.1906.08936.
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#. [38/LOGOS-CONSENSUS](https://github.com/vacp2p/rfc/pull/512)
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#. [Rocket, Team, Maofan Yin, Kevin Sekniqi, Robbert van Renesse, and Emin Gün Sirer. “Scalable and Probabilistic Leaderless BFT Consensus through Metastability.” arXiv, August 24, 2020.](https://https://doi.org/10.48550/arXiv.1906.08936) TODO: add IPFS
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