Everything you need to know about ZK testing

By Jay White, Co-Founder and Director of Space and Time Research

ZK is the crypto buzzword of the year, and for good reason, but if you’re not a cryptographer or developer, you might be wondering: what exactly is a zero-knowledge proof (ZK proof)?

The central principle behind ZK tests is simple but profound: they allow one party (the prover) to efficiently demonstrate to another party (the verifier) ​​that they possess certain knowledge without needing to reveal the details of that knowledge.

The concept had its origin in the innovative work from a few academic researchers in the mid-1980s and has since become a practical mechanism for verifiable computation and laid the foundation for the modern Web3 ecosystem, where ZK testing is becoming increasingly comprehensive.

While ZK proofs existed in theoretical cryptography long before the rise of blockchain, it is the decentralized nature of the latter that has propelled ZK proofs to the public’s attention. Blockchain, in essence, is a public ledger. Every transaction, no matter how trivial, is recorded and anyone can see it. But while transparency is one of blockchain’s greatest strengths, it is also its Achilles heel when it comes to user privacy.

That’s where ZK started to show its power.

ZK tests address the dichotomy between transparency and privacy in the blockchain space. They allow transactions to be validated without revealing transaction details, thus preserving user confidentiality and maintaining the immutable nature of the blockchain. In the mid-2010s, projects such as Zcash began building ZK protocols that offer private transactions, leading to a surge in interest and adoption of ZK in Web3. But over the past decade, the Web3 use case for ZK testing has evolved from simple privacy preservation to arguably one of the most important advancements for blockchain technology: verifiable off-chain computing.

Before we can highlight the importance of verifiable off-chain computing, we have to talk about the extreme limitations of smart contracts. Smart contracts are inherently limited in three key ways:

1. Types of data they can access: Smart contracts can only access the most basic data points on-chain (such as wallet balances) and cannot natively access most on-chain data , even as simple as token prices, nor to any off-chain data. .
2. Blockchain Storage Capacity: Blockchains are not designed to store large amounts of data. Doing so is prohibitively expensive and resource intensive.
3. The logic they can execute: A smart contract can only execute very basic conditional logic without the need for exorbitant gas fees.

Without a way to solve each of these problems, the blockchain cannot scale to meet the growing needs of a growing Web3 ecosystem. Fortunately, as Web3 has evolved, so has ZK. While projects like Link of the chainThe Decentralized Oracle Network (DON) and the Cross-Chain Interoperability Protocol (CCIP) have elegantly solved the first problem, several ZK protocols are working to solve the other two.

The most elegant way to solve the limited storage and computation of the blockchain is to move some of the data and computational work off-chain. The idea that you can take actions off-chain and use a ZK proof to succinctly and trustlessly communicate a summary of those actions to the main chain without transferring all of the underlying data has ushered in a new paradigm for blockchain technology. Let’s take a look at some of the protocols being built in this space.

Solving Storage: Decentralized Storage Tested by ZK

A well-known solution to the blockchain storage problem is decentralized off-chain storage networks. Instead of storing large amounts of data, the blockchain only has to store smaller references to that data as it is stored on the off-chain platform.

However, simply moving data off-chain is not enough; To ensure that off-chain data remains available and unaltered (to reconnect to a smart contract), you need a ZK proof. Filecoin Mail is a great example of this implementation: it provides periodic cryptographic proof of continuous data storage, fostering trust in the network while alleviating the data load from the main blockchain.

Solving for Computing: Transaction Summaries

Perhaps modeled after ZK, ZK-rollups have emerged as the preferred solution to the growing demand for faster and cheaper transactions on L1 like ethereum. Instead of processing each transaction individually on the main chain, which can lead to congestion and higher gas fees, ZK rollups remove the computational heavy lifting from the chain, aggregating multiple transactions into a single “rollup.”

For every large batch of transactions processed off-main chain, only a single, compact proof is sent to you, providing cryptographic evidence that these transactions were correct. The main chain remains secure without being directly involved in verifying each individual transaction. ZK rollups not only improve transaction processing speed, but also conserve mainchain resources, significantly increasing throughput and reducing transaction fees. Some of the most notable ZK rollups include Polygon’s technology/polygon-zkevm” data-wpel-link=”external” target=”_blank”>zkEVMMatter Laboratories zkSyncand Starkware STRONGEx.

For an in-depth look at zk-rollups, check out our podcast with Starkware’s Gal Ron:

The next generation of ZK

But while solutions like ZK Proofs on Decentralized Storage and ZK Rollups have certainly laid the groundwork for expanding the limitations of the blockchain, a critical piece is still missing. On the one hand, decentralized storage solutions are just that: storage.

While storage itself is an important tool, the inability of these platforms to perform any type of “computing” beyond simple data retrieval severely limits the use cases they can support. And ZK rollups, although powerful processing solutions that cover a wide range of computing functions, still don’t fill the gap completely.

Powering applications at scale

So let’s get back to the idea of ​​scaling the blockchain: what does that mean and what does it look like? If you compare the blockchain stack with the traditional application stack, you will notice some obvious differences. In traditional SaaS, applications (at the most basic level) are based on three steps:

1. Retrieve the result of a query: ask a question about data and get an answer.
2. Perform an action: Perform a task based on the response.
3. Update a status: Tell the system that you have completed the task.

Let’s see examples:

Example 1: social media platform

1. The app queries the content associated with a user’s connections and gets a ranking of what’s most relevant.
2. The app displays the content in the user’s feed and the user views the content.
3. The app updates the backend state by recording content viewing/engagement (which then adjusts the algorithm).

Example 2: Travel booking website

1. The application consults available flights and obtains the most relevant ones.
2. The app promotes relevant flight options to the customer, and the customer selects and purchases a flight.
3. The application updates availability and records the customer’s reservation details.

In Web3, the blockchain serves as a state management layer and smart contracts execute actions as arbitrary code, but a key component is still missing: queries. Smart contracts have no way to ask questions about the data. Even something as simple as “what wallets have ever had 2 NFTs from this collection on my chain?” it cannot be answered natively by a smart contract. If we are going to realize the vision of Web3 and scale the blockchain to meet the demands of enterprise applications, we have to give smart contracts a way to trustlessly ask questions about data on their own chain, on other chains, and off the chain.

Database computing (essentially, the ability to ask questions about data) has historically been relegated to centralized, trusted solutions, such as PostgreSQL (for simple queries) or Snowflake (For analysis). Decentralized databases exist, but they do not operate at the same scale or performance as their centralized counterparts.

And while ZK has evolved to support verifiable off-chain computing, the solutions that have emerged are limited and fragmented, and no ZK projects address the most important missing piece of the Web3 stack: queries.

That is why the team Space and time Constructed SQL Test: A ZK test that juxtaposes the scale of a data warehouse (an enterprise-scale database) with the verifiability of a blockchain. SQL testing demonstrates that queries run against a database are correctly calculated with the correct data and that both the query and the underlying data have not been tampered with. This allows smart contracts to access off-chain database computing in a verifiable way, fills the query gap in Web3, and allows developers to create data-driven NFTs, protocols, and on-chain financial instruments. reliable.

Proof of SQL allows Space and Time’s own decentralized data warehouse to serve as Web3’s verifiable compute layer, but can also connect to any SQL database, centralized or decentralized, to provide verifiable query results to smart contracts.

As we stand on the brink of a decentralized future, the importance of ZK testing in reshaping Web3 cannot be understated. The arrival of solutions like Proof of SQL highlights the transformative power of ZK, expanding its usefulness far beyond mere transactional privacy. The continued evolution and adoption of ZK technology will be critical to creating a decentralized future that combines scale and trustlessness, ushering in new paradigms of security, efficiency and transparency.

About the Author

Jay Blanco He is co-founder and head of research at Space and Time. His primary focus is the research, design and implementation of Space and Time’s innovative database protection mechanism, called SQL Testing.

Prior to Space and Time, Jay was a Mathematics professor and his research focused on computational mathematical problems. Jay’s background in algorithmic development and algebraic research has uniquely positioned him to merge the theoretical mathematics of cryptography with the scalable implementation needed to create cryptographic guarantees for enterprise-scale databases. At his core, Jay is a passionate problem solver, visionary and researcher who is building an essential solution for Web3 infrastructure.

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