Web3 privacy layers overview from embedded to total anonymity

“To privacy or not to privacy? That is the question”. Web3 has an almost mystical approach to privacy that constantly changes with the “help” of Chainalysis or the Tornado Cash case. Today hundreds of companies facilitate their version of privacy visions for the Web3 future. Let’s try to distil their areas of privacy preservation.

Embedded privacy

Definition: network-level privacy that allows seamlessly deploy privacy within dApps. Privacy by default.

Example:?Manta Network

A mass-market approach to privacy-enhancement that enables developers to incorporate privacy-as-a-service with ease. Helping humans use dApps or protocols without even realising that they are protected (it’s a default state). Similar to the role of HTTPS in the life of the average internet user.

Pros

• Default access to privacy simplifies its onboarding for humans
• It avoids hard moral choices for humans

Cons

• Privacy advocacy is delegated to projects
• Possible missing privacy consent (primarily related to third-party requests)

General comment

PaaS (Privacy-as-a-Service)?— normalises access to privacy without requiring developers to hire expensive specialists like cryptographers & ship privacy faster to humans. It allows privacy-preservation culture to become routine. But the question remains the same: how to help humans understand the importance of privacy protection in times of Bitcoin transparency and ConsenSys data collection?

Programmable privacy

Definition: a configurable approach to privacy that lets human disclose their transactions to third parties.

Example:?Aztec

It lets humans setup their privacy features so that transactions can be revealed from the accountant to law enforcement units. Moreover, it’s compliant ready, so it transmits fight with so-called bad actors who could compromise the system.

Pros

• A golden ticket for DeFi users allowing them to KYC or AML their both identity & transactions.
• Government transparency allows to pay taxes, collaborate with accountants and play by the rules of the state agents.

Cons

• Governments, enterprises & other third parties abuse your private data without knowing it. Programmable privacy could allow them to continue.
• Data processors abuse the current state of GDPR consent through biased UX/UI forms that trick humans into allowing companies to be aggregated & used data for profits or surveillance. Web3-configurability could fall into this trap as well.

General comment

Programmable privacy is a threat to illiteral in tech humans. If it falls off the ethical tech slope — it could be a continuation of the Web2 data exploitation machine. Especially when ethics & human-centric narration is missing from slang-heavy web3 companies’ social media & conference exposure.

Enterprise readiness

Definition: enterprise-grade & government-compliant privacy protection standard.

Example:?NYM

Network-level privacy reimagines how data flows & activates through the computers — mixnet. It allows third parties like fintech, healthcare and personal data sectors to access or send data cross-borderly without any leakage. Those raising a bar of data economy powered up by uncompromised privacy-enhancing tech.

Pros

• Accessible to human rights activists from Iran to Russia
• Facilitates network-level privacy standard

Cons

• Google is a corporation mentioned for adoption. In times when Google is a driver of surveillance capitalism.
• Legal implications and challenges for the network in relation to subpoenas from law enforcement units (potential ban in countries like Russia).

General comment

High-scale privacy enhancement protects humans from accidental data leakage — that's happening now. The latest privacy policies scandals from ConsenSys to Uniswap show the importance of network-level privacy that will help to set boundaries between partial privacy & surveillance services.

Nym’s challenge is balancing social justice warriors’ default tool & enterprise-grade clients’ incorporation with all their bureaucratic apparatus from the Data Officers to Nasdaq prices protection culture.

Total anonymity

Definition: human-centric privacy without compliance compromises & invisible to law enforcement units.

Example:?DarkFi

“Totalitarianism cannot be defeated through compliance” statement embodies DarkFi ethos aiming to revolt against surveillance capitalism & dictatorship. Unlock the ability to make Autonomous Political Formations (DAOs + DeFi).

Pros

• No compromises on data ownership
• No romanticising of government surveillance apparatus

Cons

• Inaccessible to general masses
• On the absolute edge of being prosecuted by law enforcement units from all over the world

General comment

Would DarkFi become a standard tech behind Rojava alike social phenomenon? Creating a self-sufficient layer of tech for the human states (anti-network or a startup state activity; read: Balaji & Silicon Valley bros vision of the world). It’s an intriguing quest & great challenge: how far would we go to preserve our privacy & data ownership?

Summary

Different companies introduce a broad range of privacy preservation. So they force privacy-centric narration to flourish & be open to interpretation.?

Moreover,?privacy has become an ideology & could easily answer the question of which political spectrum you are. Helping to filter through the web3 buzzwords towards decentralisation ethos beyond capitalist implications.

Are privacy services accessible now to non-tech people from so-called underdeveloped countries??No. So it’s important to think now about the inclusion & diversity of humans using privacy with ease on the road to privacy-enabling tech. Especially from the point of?human consent with data policies in Web3?or?humanistic UX/UI?that will challenge Web2 norms on maximising profits from human attention & data.

That’s where?Alliances, workshops, frameworks & other pro-privacy educational activities could flourish. Making web3 a better & more healthy environment.

Especially?when Web3, step by step, falls into an open arm of KYC, AML, subpoenas, government surveillance, state agents prosecutions and compliance-compliance-compliance.

Part of the Web3privacy now?research project.