The next battleground for military strategists: generating ZK proof market

Proof markets and proof networks are the two main approaches. Prove that the market is like an open market.

Written by: Yiping, IOSG Ventures

TL, DR;

• ZK technology is mainly used to improve the scalability, privacy and credibility of various projects (such as Starkware, zkSync, Scroll, Mina, Risc0, Giza and EZKL).
• ZK technology requires a large amount of computing power, resulting in a computing overhead of 10^4 to 10^6, posing a challenge to the infrastructure team.
• The main methods for generating ZK proofs are Proof Markets and Proof Networks. Proof Markets operates as an open market for trading ZK proofs, while Proof Networks has in-house servers that provide a cloud-like experience for generating proofs. *The Proof Market approach allows for flexibility and cost-effectiveness as it promotes an open market where ZK proof transactions can be conducted without the need for high-end server management.
• The Proof Network approach provides a smooth and developer-friendly experience and provides a solution that generates evidence quickly and reliably with less focus on market mechanisms. In theory, it can generate proof quickly, because it also takes time to match orders in the proof market.
• Challenges include difficulties in testing and debugging, the emergence of new security issues, possible vendor lock-in, higher costs under certain usage models, and loss of token utility.
• Leading players are likely to be those companies with the greatest demonstrated need for in-house ZK, as they can leverage existing infrastructure and specialized teams to maximize hardware utilization.
• Emerging applications include ZK Coprocessors, ZK Attestation, ZKML, and ZK Bridges, which create greater demand for generating ZK proofs.
• In the ZK space, decentralized evidence networks are driven by the blockchain industry’s preference for security, censorship resistance, and privacy, although ZK’s inherent security means that these advantages do not require decentralization as a prerequisite. For Zk, performance is the main focus.

Introduction

Growing ZK Demand

After years of research in the field of zk and huge improvements in performance, zk has finally been used in practical applications. Talented engineers apply ZK to:

• Scalability
• privacy
• Data credit

There are many interesting projects that depend on zk, such as Starkware, zkSync, Scroll, Mina, Risc0, =nil;Foundation, EZKL, Giza, Polygon and Manta. These projects steadily and continuously generate zk proofs every day. The most popular zk use case currently is zkRU which is used to solve Ethereum's scalability issues. Over the past month, millions of dollars have been spent on Ethereum/Ethereum L2s.

Source: A strong increase in ZK verification cost over last year.

This chart produced by the Near team shows the gas consumption of zkSN(T)ARK on Ethereum and L2s. It includes popular ZK projects like zkSync, Polygon, Aztec, Tornado Cash, Loopring, Worldcoin, Tailgun, Sismo, StarkNet and ImmutableX and dydx.

Compared to zkStark, zkSnark accounts for 80% of the total cost in verification. Among all these projects, Worldcoin has the highest verification cost, followed by zkSync. Verification costs approximately $2 per worldcoin. Authentication costs approximately $30 per zkSync.

Demonstrating Infrastructure Burden

ZK solves the scalability problem, but at a cost. It requires a lot of computing power. ZK brings a lot of computational overhead, and the Rollup team needs to deal with this problem. @_weidai estimates that using today's ZK technology will have a computational overhead of 10^4 to 10^6. In theory, we can achieve 10 times the computational overhead with dedicated circuits. If the abstraction layer of the virtual machine is added, there will be 100 times the computing overhead.

The chart below depicts a graph of computing power based on year-on-year growth according to Kumoy's Law. After 2000, chip efficiency increased by 10 times every ten years. If we compare computing power against the year 2000, it will reach 784 times in 2025. This also shows that the current ZK calculation is still not on the same order of magnitude as that in 2000.

Source:

Please think about this carefully. We are trying to increase transaction volume by 10 to 100 times to ZKRU. As the transaction volume increases, we will also face a computational overhead of 10^4 to 10^6. These numbers put tremendous pressure on the ZKRU infrastructure team. Leading ZKRU teams are using high-end machines with at least 200 GB of memory and have talented operations staff to handle these infrastructure complexities.

So what does it mean for a small team if they want to launch a ZKRU or build a third-layer solution with the ZK technology stack? If an independent developer wants to build a ZK Dapps, how do they buy these high-end servers and operate them properly?

Now, starting a ZKRU is not difficult. You can use ZK Stack and follow the instructions in the documentation to deploy a new ZKRU. The hardest part is getting the high-end infrastructure to work. Managing a fleet of servers is much more difficult than day-to-day maintenance of our personal laptops.

Additionally, hardware acceleration is not plug-and-play; each team will need to configure their servers differently depending on the zero-knowledge proof system they are using.

Ensuring high availability is also a tricky topic. What if tons of users start minting Ordinals on your ZKRU and you suddenly face 1000x throughput? Even an experienced team like Arbitrum was down for several hours due to the surge in Ordinals transactions.

Generating large numbers of zero-knowledge proofs requires high-end server support. For small and medium-sized teams, setting up and maintaining a fleet of high-end servers can be a heavy burden. To better help groups simply and quickly adopt zero-knowledge technologies, the Emerging Project attempts to help these groups deal with all computing infrastructure complexities.

Prove the market

Source: IOSG Ventures

Proof markets and proof networks are the two main approaches. Prove that the market is like an open market. To generate a proof, a user needs to find a counterparty willing to sell the proof for a certain price. The proof network works like a traditional cloud service, developers submit their circuits and inputs, and a centralized load balancer allocates internal servers within the proof network to generate proofs for users.

Proof markets are a popular approach in ZK proof infrastructure. The Proof Market is an open market where buyers and sellers trade ZK Proofs. The ZK Proof market team does not need to care about ZK Proof hardware or own high-end servers, they focus on ZK Proof transactions and verification mechanisms to attract third-party hardware vendors.

Proving that the market is a more open approach. It welcomes third-party hardware vendors. As long as there is a seller with such a certificate, the buyer can purchase the ZK certificate at a USD price. When verifying proofs, everyone in the market does not need to reach consensus, only market operators bear the responsibility for verification. In the proof market, zkDapp developers submit a ZK proof order, including price, generation time, timeout and public input. The third-party hardware vendor will then accept the order and generate a proof.

Demonstrate that the economic structure of markets is simple. Proof generators need to stake. If they generate the wrong certificate or fail to provide it by the deadline, they can be fined. Proof generators with more stake will be able to generate multiple proofs simultaneously.

The major players in the certification market industry are =nil and Marlin.

=nil Foundation

Prove that there are sellers and buyers in the market. The buyer is the dApp developer. They pay the seller a fee to generate the certification. There are many factors that influence the price of a certificate. Major factors include circuit size, proof system, generation time, and input size.

Here’s how the =nil proof market works:

1. Prove that the requester sends a request to the market with an expected price of c_r.
2. Prove that the market locks c_r tokens in the buyer’s account.
3. Prove that the producer sends a proposal to the market with price c_p <= c_r.
4. The proof market matches requests with proof producer proposals.
5. The proof producer generates the proof and sends it to the market.
6. The proof market verifies the proof and pays c_r - handling fee tokens to the producer.
7. Certification requesters obtain their certification and use it.

The market design provides a trading-like experience. Prove that the generated price will change in real time.

Below is a screenshot of the product for the =nil proof market.

Source:

Currently, Proof Market supports a limited number of claims, with the Mina claim proving to be the most active. Specifically, Proof Market accepts circuits based on their zkLLVM compiler and Placeholder proof system.

Gevulot

Gevulot is committed to bringing decentralization to the proof-of-proof market. Gevulot serves as an open and programmable layer 1 blockchain designed for proof-of-market. The first layer of the blockchain handles the distribution, verification and reward distribution of proof requests. The prover network leverages lightweight unikernels to achieve high performance. Gevulot uses verifiable random functions (VRFs) to distribute proof work to a small group of provers, ensuring the reliability of the system.

*Source: *

Users can deploy programs seamlessly with predictable fees, and users can set a maximum fee based on the number of cycles the program takes to execute.

Provers are rewarded through the Gevulot network and user fees, incentivizing them to generate efficient and competitive proofs. The fastest prover will receive the most network rewards. User fees will be shared equally with all nodes that complete the proof.

Gevulot supports multiple programming languages for program deployment, including C, C++, Go, Java, Node.js, Python, Rust, Ruby, PHP, etc., because Gevulot's underlying VM Nanos supports x86_64 Linux ELF binaries.

Gevulot is a general computing platform that supports different languages and proof systems. Gevulot relies on Nanos single core to ensure that the prover can easily run on different machines. All provers need to be compiled into a single single-core image.

Proof Network

Proof Network provides a more user-friendly approach to the developer experience. It operates similarly to Web2's cloud service provider. Developers send payload data through the REST API, and the proof network then returns proof to the developer. Developers do not need to care about price fluctuations and which party will generate proofs.

Heating0

Risc Zero launched Bonsai using their zkVM. With the power of zkVM, users can let Bonsai generate various declarations. For example, based on Bonsai and Risc0 VM, Zeth generates proofs for Ethereum blocks.

Source：

Succinct

Recently, Succinct also launched their new product. Rather than providing a REST API circuit, Succinct provides an approach more similar to cloud functions.

Here is the user workflow:

1. Connect to your GitHub account and deploy the circuit
2. Call the API through REST or smart contract and pass in the circuit input
3. Query results through REST API or smart contract

*Source: *

Compared with BONSAI, Succinct has the following advantages in developer experience:

• Easier management of circuit code libraries
• No need for secondary sending circuit
• One-click deployment of smart contracts for on-chain proof generation and verification
• Explore popular ZK proofs
• Check the certificate generation status on the dashboard
• Support rustx, gnark, circom, plonky2

*Source: *

Proof network or proof market

The certification marketplace provides buyers and sellers of certifications with greater pricing flexibility. It invites all hardware providers to participate, which helps reduce costs for buyers. But it's worth noting that savings can vary between individuals and businesses. Often, centralized services like Proof Network may offer free services to individuals while charging businesses high fees but providing access to VIP customer support. For example, if an enterprise plans to launch a new event or feature, the enterprise can reserve some computing power on the proof network in advance. A decentralized market may present more balanced and competitive pricing.

In today's market, proof network-based products appear to provide developers with a smoother experience. It handles all proof generation work and supports major proof systems without introducing any new complex concepts. It provides a consistent user experience. In theory, it provides fast proof generation since order matching in the proof market also takes time. If you are familiar with cloud computing, it turns out that the network is more like a stateless cloud function.

We have =nil Foundation and Gevulot working on the proof market. Succinct and Risc0 are on the proof network. Hardware companies like Ulvetanna and Cystic have also made significant contributions to improving ZK-proof performance on GPUs and developing the next generation of dedicated ZK chips.

The market proved relatively easy to launch. For the ZK infrastructure project, the proven market design can bring more hardware providers online. With its decentralized design, they can easily scale the network to meet future computing needs.

In the future, we foresee a combination of proof network and proof market designs. The goal is to provide a seamless experience for developers while integrating a proof market as a backend to facilitate the addition of additional computing resources. This is a direction Succinct plans to pursue in the near future. We are seeing similar shifts in other markets, such as Infura. Infura has its own servers, but it also plans to bring in licensed parties to provide infrastructure.

Source: IOSG Ventures

Who really needs cloud ZK infrastructure

**We believe that developers who want to reduce time to market and build lightweight, flexible applications that can be quickly expanded or updated will greatly benefit from these cloud ZK infrastructures. **

For applications with large differences between peak and trough usage, cloud ZK infrastructure will reduce costs.

For this type of application, it can be expensive to purchase a fleet of servers that are always running and guaranteed to be available at peak times. When the usage is at its lowest, it will cause a lot of waste. Cloud infrastructure can be expanded at any time to improve performance. This excess computing performance can be automatically released outside of peak times.

Who will be the leader?

From our understanding of the Web2 cloud industry, we found that those companies with the greatest computing needs tend to have leading cloud infrastructure businesses. They can take advantage of scalability, cost, teams, and innovative products.

The same applies to cloud ZK infrastructure. **We believe that those projects with the greatest need for build verification have the potential to have one of the most successful ZK Cloud Infrastructure businesses. **

For projects that generate large amounts of ZK proofs in-house, they already have extensive infrastructure, optimizers, and dedicated teams. They can also maximize hardware utilization by sharing proof resources across applications; when an application does not need to generate proofs immediately, provers can be repurposed for other purposes.

These large projects all have their own proof systems to some extent. Third-party proof infrastructure often has difficulty optimizing the various proof systems used by different large-scale projects. By providing fast and easy-to-use cloud provers, large projects can effectively expand their ecosystem of proof systems.

For ZKRU, cloud ZK infrastructure can increase its Fork usage. It is not difficult to spin up a new layer 2 or layer 3 on these ZKRUs, but maintaining the ZK infrastructure will be costly. Providing out-of-the-box and flexible cloud attesters can help attract more developers. Currently, most developers usually use OPRU SDK to build new layer 2 or layer 3 because the corresponding infrastructure is easy to manage.

Without building their own ZK infrastructure, these huge ZK projects would need to pay high fees to third-party computing providers. They are also limited in the speed of development because they cannot always customize their infrastructure to further improve performance and reduce proof costs.

Who has the greatest need for zero-knowledge proofs?

**In addition to ZKRU and layer 1 networks, we have recently seen more emerging zero-knowledge proof applications. They all have a huge need for proof generation. **

Zero-knowledge coprocessors enable smart contract developers to access past blockchain states without trust. A zero-knowledge coprocessor generates zero-knowledge proofs for these past blockchain states. This may be a more secure and less trustless alternative to graphs.

Zero-knowledge authentication helps users bring off-chain data or identity information onto the blockchain. After the authenticator verifies this data off-chain, a zero-knowledge proof is generated for it and placed on the blockchain.

Zero-knowledge machine learning makes on-chain reasoning possible. The computation provider performs the ML computation off-chain, generates a zero-knowledge proof for it, and then publishes the proof to the blockchain.

Zero-knowledge bridge is a more secure version of cross-chain bridge. It generates a proof of storage or even a proof of consensus for the source chain and places it on the target chain. This may replace the current cross-chain bridge.

What’s so special about decentralized proof networks?

Within the blockchain industry, decentralization is the most popular narrative. Decentralization brings many benefits:

• safety
• Censorship resistance
• Privacy

Zero-knowledge proofs are different from other general computations. ZK is inherently safe. Anyone can easily and quickly verify a proof, ensuring the prover's honesty. In the field of ZK, decentralization is not a prerequisite for security.

Zero-knowledge proofs focus on complex low-level details, structured into circuits. While the content within these circuits is extremely difficult to censor, censorship can still be effectively implemented by generating requesters against ZK proofs.

Privacy can be an issue for proof networks because users send private inputs to the proof network. The ideal solution would be to generate the proof locally to prevent any data leakage. This will challenge local performance. Other solutions might be a new zero-knowledge multi-party computation protocol or generating proofs in a trusted execution environment. A decentralized proof network cannot bring more privacy.

Narrative aside, censorship resistance is probably the main reason for building a decentralized proof network. Zero-knowledge proof technology is still in its infancy, and so far we have not observed any form of censorship in this space. However, the main challenge hindering the development of zero-knowledge proofs is performance. The introduction of a decentralized proof network may lead to an increase in the computational requirements for generating proofs.

in conclusion

The application of zero-knowledge proof is developing rapidly and has a wide range of applications. We expect to see zero-knowledge proofs being integrated into different technology stacks. We have already seen ZK layer1, ZK 2-layer network, ZKML, ZKVM, ZK-Email. Developers are also building ZK oracles, ZK data sources, and ZK databases. We are on the road to “ZKifying everything”. The computational overhead introduced by ZK forces developers to deploy their circuits on high-end servers. As a result, we expect demand for cloud ZK proof infrastructure to increase to help developers escape the complexities of operating these infrastructures.

In this area, our insights include:

• Proof Markets and Proof Networks are two main approaches that can help ZK dApp developers stay away from the complexity of infrastructure.
• We anticipate there will be a hybrid approach that combines proof network and proof market mechanisms.
• Not all ZK dApp developers are suitable for using cloud ZK infrastructure. Medium-sized projects with stable traffic can self-host servers to reduce costs.
• The leaders in cloud ZK infrastructure will be those projects that have a need to generate large amounts of ZK proofs, such as the leading ZKRU. They have a financial incentive to do this business.
• Decentralization is the dominant narrative in the crypto space because decentralization brings properties such as privacy, censorship resistance, and security. ZK turns out to already have some of these features. Currently, the selling point of the decentralized proof market is censorship resistance. **
• The popularity of Cloud ZK proof infrastructure is closely related to the number of ZK dApps currently on the market. While some projects initially highlight their cloud ZK-proof infrastructure as a key feature, many will eventually pivot to focus on other new narratives.