Everything You Need to Know About ToM Evidence
Written by: Jay White, Co-Founder and President of Space and Time Research
ToM is this year’s buzzword in crypto, and for good reason, but if you’re not a cryptographer or developer you might be wondering: What exactly is a zero-knowledge proof (ToM proof)?
The basic principle behind ToM evidence is simple yet profound: it allows one party (the prover) to effectively prove to another party (the verifier) that he or she possesses certain knowledge, without needing to explain the properties of that knowledge.
The concept originated in groundbreaking work by several academic researchers in the mid-1980s and has since evolved into a practical mechanism for verifiable computation, laying the foundation for the modern Web3 ecosystem in which ToM evidence is becoming increasingly integral.
While ToM proofs existed in theoretical cryptography long before the rise of blockchain, it is the decentralized nature of the latter that has thrust ToM proofs into the public eye. Blockchain is essentially a public ledger. Every transaction, no matter how trivial, is recorded and viewable by anyone. But while transparency is one of blockchain’s greatest strengths, it’s also its Achilles heel when it comes to user privacy.
ToM proofs address the dilemma between transparency and privacy in the blockchain space. They allow transactions to be verified without revealing transaction details, thus protecting user privacy while preserving the immutable nature of the blockchain. By the mid-2010s, projects such as zcash began creating ZK protocols that offered private transactions, leading to an increase in interest and adoption of ZK on Web3. But over the last decade, the Web3 use case of ToM proofs has evolved from simple privacy preservation to arguably one of the most important advances for blockchain technology: verifiable off-chain computing.
Before emphasizing the importance of verifiable off-chain computation, we should mention the extreme limitations of smart contracts. Smart contracts are inherently limited in three primary ways:
- Types of data they can access: Smart contracts can only access the most basic on-chain data points (like wallet balances) and cannot natively access most on-chain data (even as simple as token prices) or any off-chain data. .
- Blockchain storage capacity: Blockchains are not designed to store large amounts of data. Doing this is extremely expensive and resource intensive.
- Logic they can execute: A smart contract can only execute very basic conditional logic without the need for exorbitant gas fees.
The most elegant way to solve blockchain’s limited storage and computation problem is to move some of the data and computational work off-chain. The idea that you could perform off-chain actions and use ToM proof to concisely and reliably transmit a summary of those actions to the main chain without transferring all the underlying data heralded a new paradigm for blockchain technology. Let’s take a look at some of the protocols created in this area.
Solution for Storage: Decentralized Storage Proven by ZK
A well-known solution to the blockchain storage problem is off-chain decentralized storage networks. Instead of storing large amounts of data, the blockchain only needs to store smaller references to that data as it is stored on the off-chain platform.
But simply moving data off-chain is not enough; To ensure that off-chain data remains available and not modified (to reconnect to a smart contract) you need a ToM protection. filecoin‘s PoST is a great example of this application: it provides periodic cryptographic proofs of continuous data storage, increasing trust in the network while continuing to lighten the data load from the main blockchain.
Compute Solution: Transaction Aggregations
Perhaps the poster child of ZK, ZK rollups have emerged as the preferred solution to the growing demand for faster and cheaper transactions on L1s like Ethereum. Rather than processing each transaction on the main chain individually, which can lead to congestion and higher gas fees, ZK aggregations remove the computational burden from the chain and aggregate multiple transactions into a single “aggregation.”
For every large group of transactions processed on the main chain, only a single, compact proof is sent back to it, providing cryptographic proof that those transactions are correct. The main chain remains secure without being directly involved in verifying each transaction. ZK rollups not only increase transaction processing speed, but also save the main chain’s resources, significantly increasing throughput and reducing transaction fees. Some of the most prominent ZK aggregations include Polygon’s zkEVM, Matter Labs’ zkSync, and Starkware’s STARKEx.
For an in-depth look at zk-rollups, please check out our podcast with Gal Ron from Starkware:
New Generation ZK
But while solutions like ToM proofs and ToM aggregations on decentralized storage have certainly laid the groundwork for expanding the limitations of the blockchain, there is still a critical missing piece. On the one hand, decentralized storage solutions are just that: storage.
While storage is an important tool in its own right, the inability of these platforms to perform any type of “computing” beyond simple data retrieval severely limits the use cases they can support. And although ZK aggregations are powerful processing solutions that cover a wide range of computing functions, they still don’t completely fill the gap.
Hardening Applications at Scale
So, back to the idea of scaling blockchain; What does this mean and what does it look like? If you compare the blockchain stack with the traditional application stack, you will notice some distinct differences. In traditional SaaS, applications are supported (at the most basic level) through three steps:
- Get query result: Asking questions about data and getting answers.
- Execution of an action: Performing a task based on the response given.
- Update a status: Notifying the system that it has performed the task.
Example 1: Social media platform
- The app queries the content associated with the user’s links and gets a ranking of the most relevant ones.
- The app displays content from the user’s stream and the user views the content.
- The app updates the backend state by recording content views/interaction (this then adjusts the algorithm).
- The app queries available flights and retrieves the most relevant flights.
- The application introduces the relevant flight options to the customer and the customer selects and purchases a flight.
- The app updates availability and saves customer booking details.
Database computing (essentially the ability to ask questions about data) has historically been relegated to centralized, reliable solutions like PostgreSQL (for simple queries) or Snowflake (for analytics). Decentralized databases exist, but they do not operate at nearly the same scale or efficiency as their centralized counterparts.
While ZK is evolving to support verifiable off-chain computing, emerging solutions are limited and fragmented; There are no ZK projects that deal with queries, which is the most important missing piece of the Web3 stack.
That’s why the team at Space and Time created SQL Proof: a ToM proof that combines the scale of a data warehouse (an enterprise-scale database) with the verifiability of a blockchain. SQL Proof proves that queries run against a database are calculated correctly on the correct data, and that both the query and the underlying data have not been modified. This allows smart contracts to verifiable access to off-chain database computing, filling the query gap in Web3 and allowing developers to build trustworthy, data-driven NFTs, protocols, and financial instruments on-chain.
SQL Proof enables 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 precipice of a decentralized future, the importance of ToM evidence in reshaping Web3 cannot be ignored. The emergence of solutions such as Proof of SQL highlights the transformative power of ToM and extends its utility far beyond pure transaction confidentiality. The continued development and adoption of ZK technology will be instrumental in creating a decentralized future that combines both scale and trustlessness, pioneering new paradigms of security, efficiency, and transparency.
about the author
Jay White is the Co-Founder and Head of Research at Space and Time. His primary focus is on the research, design and implementation of Space and Time’s innovative database tampering protection mechanism called Proof of SQL.
Prior to Space and Time, Jay was a Professor of Mathematics whose research focused on computational mathematics problems. Jay’s background in algorithmic development and algebraic research has placed him in a unique position to combine the theoretical mathematics of cryptography with the scalable application required to create cryptographic guarantees for enterprise-scale databases. At heart, Jay is a passionate problem solver, visionary, and researcher who has created a fundamental solution to the Web3 infrastructure.
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