web3privacy/Web3privacynowplatform/scoringmodel/Scoringmodel_techies.md

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Privacy scoring modelling > Web3privacy now analytical platform

General

Scoring Techie
Immutability +
Decentralised throughout, including hosting +
Permissionless & accessible to all +
Open-source +

Docs

Scoring Techie
read the documentation +
Good and comprehensive documentation +

Third-party analysis

Scoring Techie
Where's the code? Has it been audited? +
Validation by trusted and respected independent scientists and researchers +

Team

Scoring Techie
ideological team +
Reputation of the team +
is it purely marketing oriented, or it seems created by researchers/developers, are the developers anons? +

Privacy policy

Scoring Techie
Privacy Policy content +
Non-vague and non-intrusive privacy policy +

Infrastructure

Scoring Techie
How much to run a node +
Where are the nodes +
Number of nodes/servers/ -> the larger the footprint the best privacy +

Storage

Scoring Non-web3 person assesment Web3, but non-tech assesment
e2e encrypted LOCAL storage - +
What user information is stored? (username, IP address, last connection, wallets associate, etc) - +
Where is it stored? (centralized server, certain jurisdictions, on-chain, in browser/local cache) - +

Data aggregation

Scoring Non-web3 person assesment Non-tech assesment
no email or tel nr for signup + +
control over personal data - -
does not implement KYC or AML + +
Metadata privacy / Minimal to no metadata capture - -

Traction

Scoring Non-web3 person assesment Non-tech assesment
Amount of transactions + +
number of people using it + +
is it famous + +
Latency - -
Time of test and battle-tested code - (e.g. how BSC had passed the stress time of withdrawals with FTX drama or crypto schemes such as ECDSA with more than 2-3 decades alive) - -
Cost - +

Governance

Scoring Non-web3 person assesment Non-tech assesment
DAO structure (if applied) - +

Privacy execution

Scoring Non-web3 person assesment Non-tech assesment
How is it being transmitted? (encrypted, unencrypted, offuscated, etc) - -
Combined those encryption methods effectively (holistic solution) - -
Confidentiality of transactions - -
the ability to hide transactional data from the public - -
strong encryption algorithms - -
If the speed in connection is too fast, there most probably no privacy there and rather a direct channel between user - app - -
p2p / no central server - -
Trustless - No ID required (this is where ZKs are useful) - +
Usage of ZK - -

Product-centric

Scoring Non-web3 person assesment Non-tech assesment
Onboarding steps + +
Usability - for end users or in the developer experience if it is a B2B project. + -

Testing

Scoring Non-web3 person assesment Non-tech assesment
Ability to run part of the service and verify for myself - -
try to trace a transaction - -
There is a way to verify the code I think is running, really is running e.g. attestation service - -
Other tooling to verify e.g. block explorers - +

Other

Scoring Non-web3 person assesment Non-tech assesment
Entropy (non-trivial to estimate, different measurements for type of service). Some examples: https://arxiv.org/abs/2211.04259 or https://blog.nymtech.net/an-empirical-study-of-privacy-scalability-and-latency-of-nym-mixnet-ff05320fb62d - -
Censorship-resistant (how hard it's for a powerful party to block/censor a given service) - -
Precise description of the concrete privacy properties. Privacy is complicated, so if they don't say exactly what they protect, then its likely vapour - -
Doesnt sell your data - -
protects against a global passive adversary - -
strong secure anonymity tech - -
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 - -

Huge thanks everyone who contributed! I make it anon now, but will thank everyone (who would liked to be credited) once a scoring model will be published on GitHub for community evaluation.

2. My personal notes on privacy scoring (they were made before communal survey)

Sketches what could be put inside privacy-solutions scoring model (note: think of these as questions to experts for a workshop on scoring ideation).

Key observations

Topic Observation
Broad range of different takes on privacy assesment Privacy experts have around 50+ tips
Tech-centricity of assesment Majority of the expert takes are hard to execute by non-tech people (they need info-help!)
Privacy assessment takes enormous time Time-To privacy-fit - potential for analytical service
Privacy literacy isn't enough The scoring model demand both "decentralisation", "open-source" & "privacy" topics understanding
Mix of objective & subjective takes Scoring criteria are different from objective (example: transaction traceability) & subjective (example: backed by a16z crypto) takes

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 assessment (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 the community
  • Is there 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 Korean govs))

Data aggregation policies

Reference: https://tosdr.org

Centralisation level (incl KYC)

Reference: https://kycnot.me/about#scores