diff --git a/Web3privacynowplatform/Scoringmodel.md b/Web3privacynowplatform/Scoringmodel.md index f540246..49e869d 100644 --- a/Web3privacynowplatform/Scoringmodel.md +++ b/Web3privacynowplatform/Scoringmodel.md @@ -2,54 +2,6 @@ **Note**: _final scoring model shouldn't be too complex to execute._ -_Sketches what could be put inside privacy-solutions scoring model_ (note: think of these as questions to experts for workshop on scoring ideation). - -**Open-source transparency** -- **GitHub repos**: # of commits, # stars, date of repo creation. - -**Third party validation** -- **Security audits**: yes, no; type of audit; ammount of audits. - -**Community validation** -- Existing bugs -- White hackers assesment (like Secret Network TEE bug) -- Negative Discord, Twitter, other public feedback (product & founder-centric) - -**Team** -- Market validation -- GitHub contribution -- Track record (incl. red flag projects) - -**Financials** -- Investments -- TVL (like Aztec's L2) -- Donation-based -- Public treasury - -**Liveliness** -- How active is GitHub activity -- How active is community -- Is there a public product traction? - -**Product-readiness** -- State of product-readiness -- MVP-readiness -- Protocol (test-net/main-net) -- dApp (release timing, third party validation like AppStore/Play Store) -- network-reliability (the state of privacy in Ethereum, Solana, Avalanche etc) - -**Cross-checked data leakage** -- Complementing privacy stack data leakage (example: phone + dApp; wallet + RPC etc) -- Third party data leakage (from the hackers to state agents (think of Iran or North Korea govs)) - -**Data aggregation policies** - -_Reference_: https://tosdr.org - -**Centralisation level (incl KYC)** - -Reference: https://kycnot.me/about#scores - ## On-going community research (survey) within the privacy experts. I've asked privacy experts behind privacy-services or privacy-centric communities to contribute with their visions on how to analyse if a service is private or not. Answers were collected via chats or Survey [form](https://forms.gle/ETBEZed9LUUtLWT87) @@ -204,3 +156,52 @@ _Questions to be observed_ - Credibly neutral - ISO/IEC 29190:2015: https://www.iso.org/standard/45269.html - Anonymity Assessment – A Universal Tool for Measuring Anonymity of Data Sets Under the GDPR with a Special Focus on Smart Robotics: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3971139 + +# My personal notes on privacy-scoring (they were made made before communal survey) +_Sketches what could be put inside privacy-solutions scoring model_ (note: think of these as questions to experts for workshop on scoring ideation). + +**Open-source transparency** +- **GitHub repos**: # of commits, # stars, date of repo creation. + +**Third party validation** +- **Security audits**: yes, no; type of audit; ammount of audits. + +**Community validation** +- Existing bugs +- White hackers assesment (like Secret Network TEE bug) +- Negative Discord, Twitter, other public feedback (product & founder-centric) + +**Team** +- Market validation +- GitHub contribution +- Track record (incl. red flag projects) + +**Financials** +- Investments +- TVL (like Aztec's L2) +- Donation-based +- Public treasury + +**Liveliness** +- How active is GitHub activity +- How active is community +- Is there a public product traction? + +**Product-readiness** +- State of product-readiness +- MVP-readiness +- Protocol (test-net/main-net) +- dApp (release timing, third party validation like AppStore/Play Store) +- network-reliability (the state of privacy in Ethereum, Solana, Avalanche etc) + +**Cross-checked data leakage** +- Complementing privacy stack data leakage (example: phone + dApp; wallet + RPC etc) +- Third party data leakage (from the hackers to state agents (think of Iran or North Korea govs)) + +**Data aggregation policies** + +_Reference_: https://tosdr.org + +**Centralisation level (incl KYC)** + +Reference: https://kycnot.me/about#scores