Ethereum Ecosystem Privacy Use Cases and Projects at a Glance

Author: Anna Rose and Will Harborne, founders of ZK Validator; Translation: Golden Finance cryptonaitive

Ethereum ecological privacy project map

Preface

During EthCC, ZK Validator founders Anna Rose and Will Harborne gave a speech on the development of privacy protection in Ethereum. This article is a continuation of their presentation, which explores the privacy-preserving ecosystem of the Ethereum network in greater depth. It highlights the parties involved, as well as published and forthcoming related research.

Is privacy the same as ZK?

Before diving into the Ethereum privacy ecosystem, it is worth clarifying some terms. Over the past two years, a number of “ZK” scaling solutions have emerged, including Rollups and bridges.

Most of these solutions take advantage of the compact nature of zkSNARKs, which allow blockchains to scale, but do not achieve privacy. Therefore, despite the use of ZK in naming conventions and communication, most scaling solutions do not provide privacy-preserving features.

Other privacy protection technologies, such as Trusted Execution Environments (TEEs ), Multi-party computation (MPC) and homomorphic encryption (HE) exist, but due to its trustless nature, zero-knowledge proofs are still at the forefront of privacy protection.

Having said that, we will explore several privacy solutions in the Ethereum ecosystem, including those using ZK and others that rely on different technologies.

What is the current privacy use case for Ethereum?

As we all know, the main use case of blockchain is decentralized finance ( DeFi). Meanwhile, the main use case for privacy apps is private money transfers. However, in our research, we found that the field of decentralized identity verification is the fastest growing area in the entire privacy ecosystem of Ethereum.

Of course, there are other use cases, such as private computing, gaming, private voting, and ZKML, etc.

Private Transfer on Ethereum

In this part, we discuss projects focused on ensuring the privacy of peer-to-peer transfers. There are two categories of this use case: coin mixing services and dApps. Although they both have the same purpose, the way they ensure privacy is different.

Coin Mixing Service

In the blockchain environment, currency mixing services are privacy-enhancing services that can increase the anonymity of transactions. They obfuscate and delay transactions by combining multiple cryptocurrency inputs from different users, and then distribute the output to a different address than the original, making it difficult to trace funds on the blockchain and obfuscating Link between sender and receiver addresses.

Working principle of Tornado Cash

The degree of privacy provided by a coin mixer depends on its trust model. Centralized mixing requires users to trust the service operator not to misuse data, while decentralized mixing uses cryptographic protocols to achieve privacy without relying on a central entity.

Tornado Cash: is a currency mixing service based on zkSNARK. However, it has lost importance due to OFAC sanctions. Currently, there are no other significant mixing services in the Ethereum ecosystem.

Layer 2s

However, an alternative solution to achieve private transfers does not require the use of currency mixing services. In fact, the current trend to achieve private transfers is mainly focused on second-layer solutions. Here are some Layer 2s that have implemented this use case:

**Findora:**Findora ZK is a privacy-enhancing layer 2 solution on Ethereum, using Ethereum for consensus and verification. It uses Succinct Non-Interactive Parameters of Knowledge (SNARKs) in Ethereum smart contracts on the first layer to verify state transitions and ensure the correctness of rollups. The second-tier ledger provides privacy for payments, similar to Findora OG, and uses zero-knowledge proofs to achieve interoperability with Ethereum, enabling private transfers and confidential transaction data.

Aztec: This is the upcoming Layer 2, providing public and private smart contract execution. In the second layer, developers can achieve private transfers by using zkSNARKs. Aztec is billed as the first programmable privacy extension on Ethereum. They departed from the common EVM design in their design and used their own programming language Noir in order to achieve programmable privacy for dApps builders.

Nightfall: This is a “zk-optimistic rollup” designed by Ernest & Young in collaboration with Polygon, which uses zero-knowledge proofs (ZKPs) to keep transaction information confidential, making it suitable for commercial payments, and uses fraud proofs to ensure correctness.

Privacy Layer1 (Shielded Pool)

**Namada:**Namada is a privacy PoS layer 1 for cross-chain assets. Namada interoperates with Cosmos chains via IBC and with Ethereum via a trusted minimal bridge. Namada enriches the privacy ecosystem by providing the largest possible unified privacy set in multiple chains, and complements the functionality of other chains by providing privacy shielded actions for other chains. All assets share an anonymity set, enhancing privacy protection.

Privacy-Preserving dApps

Firn: is a Zether-based protocol that can realize private transfers of deposits, transfers, and withdrawals, using privacy protection methods.

Nucleo: is a dApp that provides private multi-signature for asset sending.

Privacy ID

Indeed, applications have emerged specifically to provide identity privacy on Ethereum. All of these applications attempt to address the fragmented identity problem online while retaining control and privacy of personal information.

Applications that use ZKPs to preserve privacy are:

PolygonID: This platform is based on expressive claim standards, which have distinct advantages over non-fungible tokens (NFTs) and verifiable certificates (VCs), which limit their expressiveness and Compositionality hinders their applicability. Using the Circom ZK toolkit, Polygon ID is able to compile zero-knowledge cryptographic constructs, known as zkSNARKs circuits, reducing complexity and increasing efficiency. Polygon ID provides on-chain verification, allowing private and trustless execution of user interactions without relying on intermediaries.

Sismo: Sismo is a platform that utilizes Zero-Knowledge Proofs (ZKPs) and privacy-preserving technologies to provide users with greater authority over their personal data. At the heart of the Sismo solution is Sismo Connect, which provides a smooth single sign-on (SSO) process, allowing users to selectively disclose personal data to applications while maintaining privacy.

Worldcoin: This project aims to prevent the proliferation of robots and AI by encrypting and storing biometric data. When needed, the system generates a ZKP to confirm identity. The project has received concerns from community members about the privacy, ethical and security risks of storing biometric data.

Violet: is a set of architectures focused on compliance and identity infrastructure, with options for customization. It provides a standardized method for issuing compliance credentials specific to individual transactions, allowing authorized participants to make only authorized on-chain function calls. Violet prioritizes data privacy and sovereignty, avoiding storing personally identifiable information on-chain. The processes and mechanisms described are applicable to support a variety of compliance regimes, including identification requirements like Humanbound. Violet aims to be the equivalent of OAuth-like functionality in the Ethereum network.

**Holonym:**Holonym operates as an identity bridge and mixer, hiding off-chain credentials and making them accessible on-chain to various web applications. The integration of this combined ledger, privacy-enhancing techniques, and zero-knowledge proofs enables a wide range of use cases, including on-chain authentication, anti-Sybil, digital crime prevention, and non-custodial wallet recovery. These features have implications for the Web3 ecosystem and may also have the potential to enhance the security and privacy of the internet, addressing issues such as crime, sybil attacks and data leaks.

Privacy Computing

Decentralized Privacy Computing (DPC) is an advanced paradigm that changes data processing and computing in a distributed network.

• DPC enables secure and private data processing across multiple nodes, keeping data under the control of its owner and ensuring confidentiality.

• This enables secure collaboration, data sharing and computing without trust and privacy protection.

In addition, integrating smart contracts can enhance the functionality of DPC, enabling transparent and automatic execution of predefined tasks through cryptographic protocols and zero-knowledge proofs, thereby ensuring strong privacy guarantees.

In the Ethereum network, there are two important protocols focused on making this happen: Aztec and Polygon Maiden. Additionally, several important research papers have emerged in this area, including the following breakthroughs:

privacy computer mechanism

Privacy Vote

There have been a few ballot proposals that have sparked controversy and discussion in various communities recently. In some cases, people have tried to bribe or dissuade token holders from voting in a particular way. These events sparked discussions in the blockchain industry about a vote on privacy.

**Nouns DAO: **NounsDao in partnership with Aragon has implemented an Aztec<>Aragon solution using Noir, Aztec’s zkDSL language. This implementation scheme can realize the anonymity and confidentiality of voting and results, and eliminates problems such as voting within 11 hours, voting coercion and follow-up effect. The proposal leverages Ethereum proof-of-storage and time encryption for minimal off-chain dependencies. The process involves three stages:

1. Nouns Census uses Ethereum proof of storage to prove ownership without revealing identity.

2. Vote confusion and delayed relay to maintain the privacy of multiple Noun holders.

3. The Time-Lapse encryption service is used to ensure the fairness of voting and the decryption of aggregated votes.

With this approach, Noun owners can prove ownership, keep voting private, and conduct private voting securely.

Cicada: aims to enable continuous private counting of votes by using cryptographic primitives not previously used on-chain. It leverages time-lock puzzles and homomorphic time-lock puzzles, enabling secure and private voting without counting agencies or other trusted parties.

Cicada is designed to minimize trust and ensure censorship resistance in a blockchain environment, making it a practical and efficient solution for on-chain privacy voting. Time-locked puzzles allow ballots to be submitted as encrypted puzzles that can only be revealed after a predetermined time, ensuring confidentiality is maintained during the voting process.

To prevent vote manipulation, voters must submit a zero-knowledge proof next to their ballot, proving the validity of the ballot. Cicada also offers the option to combine an anonymous voter eligibility protocol with it for unlimited ballot privacy.

Privacy Games

There is undeniable growth in scaling solutions for on-chain gaming. But, again, most of these solutions just exploit the succinct nature of SNARKs. However, there is a use case in the gaming industry where adding the privacy properties of ZK to their stack can avoid issues like transaction queuing and thus improve user experience.

Dark Forest: is a mythical game that uses ZKPs to preserve privacy and is a fully decentralized and persistent real-time strategy (RTS) game built on Ethereum.

• The game utilizes zkSNARKs to create a cryptographic fog that allows players to keep their planet’s location and movement private.

• Players submit commitments and zero-knowledge proofs proving the validity of their actions without revealing actual locations.

• Players cannot inspect contracts for information about opponents, creating an incompletely informed game setting with strategic depth and emerging player behavior.

Privacy DeFi

Another area where privacy is needed is DeFi. On Ethereum, more and more private DeFi applications have emerged.

Panther Protocol: Provide users with interoperable, fully collateralized digital assets, utilizing zkSNARK technology. It also provides a novel price discovery mechanism for privacy. Users can deposit digital assets from any blockchain into Panther Vaults, and then use these zAssets in various DeFi applications.

**Railgun: **Using zk SNARKs enable privacy directly on-chain Smart contract calls without relying on a separate set of L2 validators or hosted bridges.

• By keeping funds within the main chain, Railgun ensures greater security and tight privacy, preventing information leakage or contamination.

• Railgun’s privacy features have potential use cases including private payroll services, MEV advantages for traders, censorship-resistant donations, anonymous analytics, and compliance with data protection regulations.

ZK ML

One benefit of using zkSNARKs with machine learning algorithms is the ability to make inferences on private or sensitive data while maintaining privacy. Our Q2 2023 ZK report highlights the role of ZK in protecting privacy.

• ZK proofs allow for machine learning inference on private or sensitive data while proving the accuracy of the computation without exposing the data itself.

• The current ZK system may not be suitable for such a system, and the future Fully Homomorphic Encryption (FHE) scheme may be more suitable. Currently, there are no active privacy-preserving ZK solutions for the ZKML algorithm.

in conclusion

Ethereum has a strong and active community focused on privacy. However, due to the increased emphasis on scalability, privacy has taken a backseat. We will likely see progress in DIDs and gaming rather than DeFi or on-chain voting, as the first two use cases would benefit greatly in terms of strong privacy measures making their value proposition viable.