The next bull market narrative? An overview of the two major technical routes and potential projects in the privacy track
Original author: Biteye core contributor Fishery Isla
Original editor: Biteye core contributor Crush
There are many excellent teams launching scaling solutions for Ethereum and the broader blockchain narrative, and scaling is not the only problem that needs to be solved.
The next key function to be implemented is privacy. The privacy track has recently become a hot topic in infrastructure investment in the primary market.
This article will introduce the implementation of two popular privacy chain technology routes, Zero Knowledge Proof and Fully Homomorphic Encryption, and also introduce related potential projects that can be watched.
First, let’s discuss a question: Does Web3 have privacy application scenarios?
01 Why does Web3 need privacy?
The existing mainstream chains are all public ledgers, and all transactions are conducted on the chain. This means that state changes containing asset information related to addresses or accounts are open and transparent.
At first, information transparency was only an incidental feature set to supervise consensus security. However, with the development of the industry, the consensus mechanism has been gradually optimized, improved and reliable, and the transparent public ledger has gradually become a feature that serves technical arbitrage:
Miners can selectively package transactions based on fees, causing transactions with lower fees to be less likely to be processed, thus forcing users to increase gas fees. What is even more worrying is front-running and censorship attacks by miners or block producers by monitoring the public ledger.
By monitoring buy orders on the chain and adding their own buy orders before retail buy orders are completed, this has led to huge security issues. In the past year, MEV has successfully extracted nearly $2 billion from the market. funds.
Such a huge and continuous outflow of funds can be said to be a huge hidden danger on the road to the development of the encryption market.
At the same time, without privacy support, users lose data ownership. The asset information and transaction information of the address may be monitored and used. This goes against the vision of Web3.
Therefore, when the scaling problem is solved, the privacy smart contract chain becomes the next urgent feature to be implemented.
In order to implement privacy smart contracts, three technical routes are currently adopted:
1) TEE (Trusted Execution Environment) solutions represented by Secret Network and Oasis Network, which have been launched but are tepid;
2) The zkVM solution based on the ZK (zero-knowledge proof) principle that has entered the public eye through Ethereum’s zk-rollup;
3) The FHE (fully homomorphic encryption) solution has only recently entered the market;
TEE technology is the most mature, and there are many related documents. Interested readers can learn about it on their own, or go to the projects mentioned above to experience it personally. Therefore, this article will focus on the more topical zkVM and FHE solutions.
02 Zero Knowledge Proof
zkEVM and zkVM
Most ZK solutions fall into two camps: those built on top of Ethereum (zkEVM) and those custom built (zkVM), and therefore may choose to build with a different set of underlying trade-offs and underlying parameters.
zkEVM is a zero-knowledge proof-friendly virtual machine compatible with the Ethereum Virtual Machine that guarantees the correctness of programs, operations, inputs, and outputs.
By being built on top of the Ethereum blockchain, the zkEVM model incorporates the strengths and weaknesses of Ethereum.
Since it is optimized for compatibility with the Ethereum network, it benefits from Ethereums large user base and is easier for developers to develop on top of it (this is due to the large number of Solidity developers and its infrastructure, including execution client) is shared).
However, this also means that its ability to incorporate zero-knowledge proofs and other privacy measures is limited to the built-in limitations of the Ethereum network.
The closer a zkEVM model comes to fully simulating the Ethereum model, the more you pay in performance because it takes longer to generate proofs.
Since calculations are done on the blockchain, every transaction is fully public and transparent, which is advantageous for some applications, but for others this lack of privacy is unreasonable. or are unsecure (for example, applications related to sensitive personal financial information).
zkVM is a virtual machine that guarantees security and verifiable trustworthiness through zero-knowledge proofs - you input the old state and program, and it returns the new state in a trustworthy way. It can optimize the environment and make integrating zero-knowledge proofs into on-chain transactions cheaper, more efficient, and even easier.
Essentially, the right zkVM makes it relatively easy for all its applications to use zero-knowledge proofs in every transaction. True zkVM is built with ZK first principles and integrated into every part of the technology stack.
Ethereum is a completely open and transparent blockchain. If developers try to introduce privacy now, its performance will definitely not be as good as a blockchain that supports privacy from the beginning.
From an engineering perspective, this is difficult because developers have to code programs that were not designed to operate on this type of field, resulting in huge and more complex circuits.
Therefore, the performance of zkVM will be better than that of zkEVM, and it is a very worthy technical solution.
There are already some solutions using zkVM that have emerged.For example, L1: Aleo, Mina, etc.; L2: Aztec, etc.The market expectations of these projects are relatively high, and the cost-effectiveness of participation is not high. Here is a zkVM project that is more suitable for ambush.
Ola Network
Ola is a scalable privacy protection and compliance optimized ZKVM Rollup platform. Its main features are programmable privacy, scalability and multi-language compatibility. Ola aims to be a universal Layer 2 scaling solution that can add privacy protection and scaling capabilities to various programmable Layer 1 blockchains.
Ola recently raised $3 million in seed funding, led by Web3 Ventures and Foresight Ventures, with participation from Token Metrics Ventures, J 17 Capital, Skyland Ventures, LD Capital and CatcherVC.
Olas main products include ZK-optimized virtual machine Ola-VM and smart contract language Ola-lang.
Ola-lang is a general-purpose language developed based on ZK-VM and has higher programmability. Developers can use Ola-lang to flexibly deploy any type of smart contract, whether it is on a public chain or an enterprise-level private chain.
The ZK-optimized virtual machine Ola-VM uses a reduced instruction set architecture to achieve better performance through complete ZK support and non-deterministic computing.
Simply put, Ola is building a Layer 2 infrastructure with optional privacy and programmability.
It allows the public chain to inherit network security and at the same time obtain functions such as privacy protection and performance expansion by deploying the corresponding verification contract.
This approach avoids sacrificing the programmability and decentralization features of the public chain. Developers can add privacy and scaling solutions to different public chains as needed without making any on-chain changes.
This not only provides customizable privacy and scalability, but also maintains the open nature of the public chain.
Currently, Ola has opened tasks in the Ola Gala to qualify for the 2024 Ola Public Testnet and receive rewards such as NFT.
Moreover, on November 10, the Ola official website opened the Devnet test network application. Developers may wish to pay attention to this application. Selected personnel can receive rewards, technical assistance, developer resources, deploy Dapp on the Ola main network and other opportunities.
03 Fully Homomorphic Encryption
Fully homomorphic encryption is a new technology applied to the blockchain. It is one of the public chain solutions that is more sought after by institutions after the ZK craze. As a new concept, there are currently relatively few projects and they are all in their early stages, making them well worth ambush.
Fully homomorphic encryption is an open issue that has been raised in the cryptography community a long time ago. As early as 1978, Rivest, Adleman and Dertouzos proposed this concept in the context of banking applications.
Compared with general encryption schemes that focus on data storage security, the most interesting thing about homomorphic encryption schemes is that they focus on data processing security.
Specifically, homomorphic encryption provides a function to encrypt private data. In the homomorphic encryption scheme, other participants can process the private data, but the processing process will not reveal any original content, and at the same time they have the secret After the user of the key decrypts the processed data, the result obtained is exactly the correct data after processing.
For example, ALICE purchased a piece of gold and wanted workers to break it into a necklace. Is there a way for workers to process the gold piece but not get any gold?
To solve this problem, ALICE can lock the gold nuggets in a sealed box with only one key. This box has two holes, and a glove is installed in each hole. Workers can wear gloves to inspect the inside of the box. Gold nuggets are processed without being able to steal any gold nuggets.
After the processing is completed, ALICE takes the entire box back, opens the lock, and gets the processed necklace.
Here, the box corresponds to the all-in-one encryption algorithm, while the worker processing corresponds to the operation of performing homomorphic characteristics, and directly processes the encryption results under the condition that the data cannot be obtained.
Fully homomorphic encryption application scenarios
In Web2, homomorphic encryption is almost tailor-made for cloud computing. Consider the following scenario. A user wants to process a piece of data, but his computer has weak computing power and cannot obtain the results in time. Then the user can use the concept of cloud computing and let the cloud help him process the data and get the results. .
But if the data is handed over directly to the cloud, security cannot be guaranteed. So he can first use homomorphic encryption to encrypt the data, and then let the cloud directly process the encrypted data and return the processing results to him.
In this way, the user pays the cloud service provider, gets the processing results, and the cloud service provider earns the fee. Fully homomorphic encryption also has the disadvantage of being limited by computing power:
Computationally expensive: Fully homomorphic encryption requires more complex mathematical algorithms and larger cipher text than traditional encryption, making operations on encrypted data slower and more resource-intensive.
Computational inefficiency: FHE (Fully Homomorphic Encryption) only supports arithmetic operations on encrypted data, such as addition, multiplication, and exponentiation. For handling more complex functions, such as sorting, searching, or string manipulation, more tedious processing is required before execution. High computing power requirements.
Fortunately, we are in an era of explosive computing power. With the advancement of FHE and Web3 development, computing power performance and cost are expected to match the requirements of FHE. Therefore, this is a good time to ambush the FHE track.
Fhenix
Fhenix is the first blockchain to adopt fully homomorphic encryption technology, which can provide encrypted data calculation functions for EVM smart contracts.
The fhEVM used by Fhenix was originally developed by cryptography company Zama, which builds open source encryption solutions for blockchain and artificial intelligence, and was integrated with Fhenix Network following a strategic partnership.
In addition, Fhenix also uses Arbitrums Nitro validator and Zamas fully homomorphic ring encryption rust library tfhe-rsr. This shows the close relationship between Zama and Fhenix.
Zamas official website shows that its company is providing FHE-based Web3 solutions for some cutting-edge Web2 use cases. For example, face recognition, voice recognition and smart contracts (which is what Fhenix is currently doing), you can expect Zame to integrate all these applications into the Fhenix ecosystem in the future.
Fhenix raised $7 million in a seed round in September this year, led by Multicoin Capital and Collider Ventures, with participation from Node Capital, Bankless, HackVC, TaneLabs, Metaplanet, and Tarun Chitra and Robert Leshner’s Robot Ventures.
Compared to zk which can only verify the data segments encrypted by it, cannot merge private data from multiple parties, and therefore cannot facilitate most cryptographic calculations, FHE allows a higher level of data security and through its"overall"Encryption capabilities enable unprecedented use cases.
Therefore, the ability to have privacy in Fhenix not only solves privacy issues, but also paves the way for hundreds of new use cases - blind auctions, on-chain authentication and KYC, tokenization of real-world assets, DAOs Private voting etc.
04 Summary: ZK vs. FHE comparison
After understanding ZK and FHE, two cutting-edge privacy smart contract solutions, many readers are still confused about the two technical routes of zero-knowledge proof (ZK) and fully homomorphic encryption.
The difference between the two, in addition to the encryption flexibility mentioned above, is also reflected in:
To summarize from a technical perspective, ZK focuses on proving the correctness and protecting the privacy of statements; FHE focuses on performing calculations without decryption and protecting the privacy of data.
From the perspective of the development of the blockchain industry, projects using ZK technology developed early. From ZCash, which only has a transfer function, to the zkVM blockchain that supports smart contracts, which is currently under development, there are more blockchains than FHE. Industry technology has accumulated; and the FHE theory was born much later than ZK and is a hot spot in the academic world. It was not until recently that Web3 projects using FHE technology for financing appeared, so the development started slower than ZK.
The common point between the two points to the development of computing power, and the development of the privacy track has enjoyed the dividends of the explosion of computing power. It is precisely thanks to the improvement of computing power in recent years that these cutting-edge technologies can truly be accessible to users.
references
[ 01 ] Beyond ZK: The Definitive Guide to Web3 Privacy (Part 2)
[ 03 ] Ola: A ZKVM-based, High-performance and Privacy-focused Layer 2 platform
[ 04 ] FHE-Rollups: Scaling Confidential Smart Contracts On Ethereum And Beyond – Whitepaper
