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Scoring model

Scoring model for privacy-services attestationResearch aimed to find out dark patterns in privacy, create comprehensive scoring model to test privacy claims on behalf of the projects Supported by Ethereum Foundation, Mask

Status: ongoing

About the Scoring Mechanism

It will incorporate both expert analysis and community input, to offer impartial resources for evaluating projects.

  • Professional scoring would be a joint R&D with the key web3 people from protocol architects to security specialists. We are collecting feedbacks from privacy experts from the Ethereum Foundation, Railgun, Waku, NYMโ€ฆ

  • In parallel to the top-down scorecard method, weโ€™ll develop and implement a bottom-up community scoring platform too (think of Metacritic exters + users scorings) -> at the end of the day itโ€™s the users who have to become the real watchdogs of the industry, signaling about flaws and shortcomings of solutions.

We interviewed 100 privacy players & gathered an MVP vision โ€” we are running a series of 1-on-1 feedback loop sessions to make the scoring model community validated.



MVPdec, 20231. Landing. 2. DeFi category scoring benchmark. 3. Easily upgradable Project data via GitHub. 4. Basic documentation.
QAjan, 20241. Bug fixing. 2. Content update. 3. Content filled by the projects themselves
V 1.0Feb, 20241. Category expansion (200 projects). 2. Scoring model major update (built by community). 2. Content update. 3. Content filled by the projects themselves (plus moderation). 5. Extended documentation.
V 2.0March, 20241. Full database synchronization (600 projects). 2. Content update (actualisation). 3. Content filled by the projects themselves (plus moderation).