How Zero-Knowledge Proofs Became Ethereum's Magic Bullets
Zero knowledge proofs are powerful cryptographic instruments that accelerate innovation on Ethereum, writes Alex Shipp.
By: Alex Shipp •DeFi News
This year, Zero knowledge proofs (zk-proofs) are making their mark as the most potent cryptographic instruments powering innovation in decentralized ecosystems.
Zk-proofs were first conceived by computer science researchers Shari Goldwassser, Silvio Micali, and Charles Rackoff in their 1985 paper, The Knowledge Complexity of Interactive Proof-Systems. Developers, system architects, and researchers in the Ethereum community — blockchain’s leading smart contract ecosystem — have spent the better part of the last three years straining their creative faculties to develop solutions — and more often, temporary workarounds. Their goal is to remedy the blockchain’s two glaring deficiencies: the capacity to operate efficiently at scale, and to safeguard user privacy unequivocally.
On both prerogatives, Ethereum’s best and brightest minds have converged on zero knowledge protocols and their ever-versatile implementations to build the next iteration of turing-complete blockchain infrastructure.
The Quest for Throughput
A zk-proof describes a mechanism whereby one party can prove to another that a given statement is true without revealing any additional information, especially the content of the statement itself. Though more immediately applicable in privacy-centric scenarios — most famously in the 2016 launch of Zcash, a privacy coin that employs zks to shield transactions — zk-proofs have risen to prominence in Ethereum’s mad search for a scalability solution that can open its array of revolutionary DeFi and NFT applications to the mass market.
Per the Satoshi whitepaper, blockchain was developed for one purpose: to circumvent authority via the formation of a censorship-resistant, decentralized system absent a single point of failure. Though a tremendous feat in system architecture, decentralization does not come without costs. In decentralized systems, processes of exchanging, storing, and verifying information take place across interdependent devices, software, and humans. That is to say, they are systems of extremely high knowledge complexity.
Unlike the streamlined processes native to centralized systems, knowledge complexity necessarily detracts from network efficiency, slowing down transaction times and increasing transaction costs for users.
Since the Cryptokitties fiasco of 2017, Ethereum has been cast in the perpetual crypto-spotlight as the poster-child of blockchain’s inherent scalability dilemma. As the industry leader in decentralized applications and users, Ethereum’s knowledge complexity limits its transaction throughput to a paltry ten transactions per second — 12 on a good day.
Since the Cryptokitties fiasco of 2017, Ethereum has been cast in the perpetual crypto-spotlight as the poster-child of blockchain’s inherent scalability dilemma.
Determined to tackle the problem, developer teams across the ecosystem spun up various preliminary solutions: State Channels, which were not EVM-compatible and required user identities and up-front capital locks; Plasma, a network of less-than-convenient Child-Chains that lacked EVM-compatibility as well; Sidechains, which operated independently from the security of the Ethereum mainchain; and Sharding, a consensus modification whose attributes and delivery dates have wavered and evolved in a manner reminiscent of broken political campaign promises.
Zks remained in the frame in the form of Zk-Rollups, a mechanism that employs zkSNARK technology to consolidate off-chain transactions via Merkle Trees and publish them to the Ethereum mainchain with a single transaction — a highly efficient model that conducted computation off-chain and used the mainchain exclusively for data storage. Although the best technical solution on tap, Zk-Rollups were not yet EVM-compatible, and could only act as payment channels. DeFi applications would have to remain on-chain until roll-ups could support smart contract execution.
In the race to support DeFi, Ethereum developer team Optimism was the first to the beat with their release of Optimistic Rollups, an EVM-compatible Rollup Chain ready for one-click dApp deployments, and all without a single zk-proof. There was only one hitch: Optimism’s Rollup depended on Fraud Proofs to publish grouped transactions on-chain, thereby requiring users to tolerate Dispute Time Delays (DTDs) for mainchain withdrawals, often upwards of one week. But with composability online, Optimism remained the best available alternative.
That was, until recent months, when Matter Labs released zkSync v2: a fully functional, EVM-compatible Zk-Rollup that employs computationally sound Validity Proofs with short DTDs. With EVM-compatibility solved for v2, zkSync and its sub-ten-minute mainchain withdrawals now stand superior to Optimism, whose OVM still depends on prolonged DTDs to confirm withdrawal transactions.
As attention and developer resources continue to migrate toward the zero knowledge realm, the reality becomes clear: as per their architects’ title of choice, zk-proofs were designed for systems characterized by high knowledge complexity, and are best fit to resolve many of the computational dilemmas facing blockchain ecosystems and their paths to adoption.
Coming Full-Circle: Keeping Privacy Where it Belongs
With the conception of DeFi, Ethereum has secured its place as the go-to hub for blockchain innovation. Sophisticated applications like those that constitute crypto’s DeFi sector necessitate state saving, and therefore Ethereum’s Turing-completeness and Account-based transaction model. Meanwhile, privacy-centric applications operate on blockchains with UTXO transaction models, where global states including account balances are handled by higher levels of abstraction such as wallet applications and block explorers.
To this point, in the mission to bring privacy to DeFi, developers have settled for bringing DeFi to privacy, either building standalone UTXO blockchains or highly centralized and opaque Layer 2 models away from Ethereum’s daunting public mainchain.
It was not until January 2019 when Ethereum’s first on-chain confidential token standard was conceived in Aztec Protocol’s EIP-1724. Aztec proposed utilizing zkSNARKs to generate private tokens on Ethereum, although a trusted setup would be required to distribute private keys. In addition, the entire obfuscation process that confers privacy to Aztec’s zk-tokens takes place on a Layer 2 of sorts. A brilliant visionary model, Aztec’s Layer 2 construct brought privacy to Ethereum for the first time. But counter to scalability, privacy’s cardinal mandate is that it must live on Layer 1 — no ifs, ands, or bridges.
A year following Aztec’s launch, the Offshift team submitted a pioneering Layer 1 PriFi solution on Ethereum slated for launch in Q1 2022. The team’s model employs Bulletproof zks, which, unlike SNARKs, do not require any element of a trusted setup, and live fully on Layer 1. To address Ethereum’s Account-based transaction model, Offshift’s protocol issues zkAssets in the form of cryptographic commitments that are exchanged between Ethereum addresses in a UTXO model, thereby allowing PriFi applications to benefit from Ethereum’s Turing-completeness without leaving Layer 1.
Although entirely unique challenges, efficient scalability and impenetrable privacy are best solved by computational tools that are designed for decentralized systems – that is, systems characterized by extremely high knowledge complexity.
Decades ahead of their time, Goldwasser, Macali, and Rackoff made abundantly clear in their 1985 paper: “Knowledge complexity helps in proving or disproving the correctness of cryptographic protocols as these are based on the secrecy of some private information and should preserve this secrecy.”
They then noted poetically, “The privacy of some information is what gives us an advantage over our adversaries.”
Alex Shipp the Chief Strategy Officer of Offshift, a PriFi (private DeFi) derivatives platform.