Skip to main content

Envisioning is an emerging technology research institute and advisory.

LinkedInInstagramGitHub

2011 — 2026

research
  • Reports
  • Newsletter
  • Methodology
  • Origins
  • Vocab
services
  • Research Sessions
  • Signals Workspace
  • Bespoke Projects
  • Use Cases
  • Signal Scanfree
  • Readinessfree
impact
  • ANBIMAFuture of Brazilian Capital Markets
  • IEEECharting the Energy Transition
  • Horizon 2045Future of Human and Planetary Security
  • WKOTechnology Scanning for Austria
audiences
  • Innovation
  • Strategy
  • Consultants
  • Foresight
  • Associations
  • Governments
resources
  • Pricing
  • Partners
  • How We Work
  • Data Visualization
  • Multi-Model Method
  • FAQ
  • Security & Privacy
about
  • Manifesto
  • Community
  • Events
  • Support
  • Contact
  • Login
ResearchServicesPricingPartnersAbout
ResearchServicesPricingPartnersAbout
  1. Home
  2. Research
  3. Lattice
  4. Privacy in Transparent Systems

Privacy in Transparent Systems

Techniques to prevent transaction tracking and profiling on public blockchains
Back to LatticeView interactive version

Privacy in transparent systems focuses on balancing the value of open ledgers (blockchains where all transactions are publicly visible, enabling transparency and auditability) with protection against transaction deanonymization (identifying who is behind anonymous transactions) and economic profiling (analyzing transaction patterns to infer personal information), recognizing that transparency has benefits but also creates privacy risks. This area grapples with the tension between regulatory requirements—such as KYC/AML (know your customer/anti-money laundering) and travel rule enforcement (regulations requiring information sharing about transactions)—and strong privacy, and advocates for zero-knowledge tools (cryptographic techniques that enable verification without revealing information) that remain broadly accessible rather than becoming privilege technologies available only to a few institutions, ensuring that privacy-preserving technologies are available to everyone, not just the wealthy or powerful.

This innovation addresses the fundamental tension between transparency and privacy in blockchain systems, where open ledgers provide transparency but also create privacy risks. By developing accessible privacy tools, these systems can balance competing needs. Researchers, privacy advocates, and technology companies are developing these approaches.

The technology is essential for ensuring that blockchain systems can provide both transparency and privacy, where both are important for different reasons. As blockchain usage grows, privacy becomes increasingly important. However, ensuring accessibility, managing regulatory compliance, and achieving adoption remain challenges. The technology represents an important area of research and development, but requires continued work to balance competing objectives. Success could enable systems that provide both transparency and privacy, but the technology must navigate complex trade-offs. The development of accessible privacy tools is a critical area of blockchain research.

TRL
5/9Validated
Impact
5/5
Investment
4/5
Category
Ethics Security

Related Organizations

Aleo Systems logo
Aleo Systems

United States · Company

95%

A platform for building private blockchain applications.

Developer
Aztec logo
Aztec

United Kingdom · Startup

95%

Developing a privacy-first zero-knowledge rollup on Ethereum.

Developer
Anoma logo
Anoma

Switzerland · Research Lab

90%

An intent-centric architecture for decentralized counterparty discovery.

Developer
Electric Coin Co. logo
Electric Coin Co.

United States · Company

90%

Creators of Zcash and pioneers of zk-SNARKs implementation.

Developer
Mina Foundation logo
Mina Foundation

Switzerland · Nonprofit

90%

Stewards the Mina Protocol, a lightweight blockchain designed specifically for zero-knowledge applications (zkApps) and identity.

Developer
Oasis Labs logo
Oasis Labs

United States · Company

90%

Blockchain platform integrating secure enclaves to enable privacy-preserving smart contracts.

Developer
Penumbra Labs logo
Penumbra Labs

United States · Startup

90%

A shielded, cross-chain network for decentralized finance.

Developer
Secret Network Foundation logo
Secret Network Foundation

United States · Nonprofit

90%

A blockchain with data privacy by default for smart contracts.

Developer
Espresso Systems logo
Espresso Systems

United States · Company

85%

Developing scaling and privacy solutions for Web3.

Developer
NYM Technologies logo
NYM Technologies

Switzerland · Company

85%

Building a privacy infrastructure (mixnet) to prevent data leakage.

Developer
Railgun DAO logo
Railgun DAO

Open Source

85%

A smart contract system that provides privacy for cryptocurrency transactions.

Developer

Supporting Evidence

Evidence data is not available for this technology yet.

Connections

Software
Software
Zero-Knowledge Infrastructure

Privacy-preserving proof systems for verifiable computation without revealing underlying data

TRL
6/9
Impact
5/5
Investment
5/5
Ethics Security
Ethics Security
Power Dynamics in Decentralized Systems

Analyzing concentration of control in validators, governance tokens, and protocol access points

TRL
4/9
Impact
5/5
Investment
2/5
Software
Software
Decentralized Identity & Reputation Systems

Self-sovereign identity with verifiable credentials and cross-platform reputation tracking

TRL
5/9
Impact
4/5
Investment
3/5
Software
Software
Real-Time Fraud & Anomaly Detection Pipelines

Automated systems that spot wash trading, sandwich attacks, and cross-chain exploits as they happen

TRL
7/9
Impact
5/5
Investment
5/5
Applications
Applications
Data-as-Value Networks

Platforms enabling individuals to monetize anonymized personal data while retaining control over access and use

TRL
4/9
Impact
5/5
Investment
4/5
Ethics Security
Ethics Security
Tokenized Society Concerns

Ethical boundaries for financializing social interactions, reputation, and civic participation

TRL
3/9
Impact
4/5
Investment
2/5

Book a research session

Bring this signal into a focused decision sprint with analyst-led framing and synthesis.
Research Sessions