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Introduction to Zero-Knowledge Cryptography

When people talk about zero-knowledge cryptography in 2024, they’re often referring to a privacy-focused use case that relies on a combination of blockchain technology, cryptocurrencies, digital wallets, and users with some degree of web3 knowledge.

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Zero-knowledge proofs (ZKPs) have existed since the 1980s, long before web3’s emergence. Therefore, why limit their application to blockchain alone? Traditional companies can—and should—adopt ZK technology without fully embracing web3 infrastructure.

At a basic level, ZKPs allow one to prove something is true without disclosing the underlying data. A prover creates a proof, a verifier checks it, and both parties remain isolated to ensure fairness. Therefore, there’s no reason this concept needs the complexities of web3.

Most organizations that would benefit from ZK technology are not utilizing blockchains and are largely unaware of web3. The industry is still young, with many still getting acquainted with Bitcoin (BTC) and Ethereum (ETH), not to mention Layer 2s and 3s.

Despite this, ZKPs have a variety of real-world applications that don’t require deep integration with web3.

Trust and Slot Machine Payouts

With zero-knowledge proofs, trust in gaming operators can be eradicated. Players can enjoy games knowing they are designed fairly. Digital gambling machines should universally embrace ZKPs, benefiting both operators and players without needing to mention “web3” or “crypto.”

For instance, DraftKings and White Hat Gaming were recently fined $22,500 in Connecticut for an online slot machine game that failed to pay winners during a week in August 2023, even with over 20,600 spins. The game falsely advertised a nearly 95% payout, meaning players lost all $20,600 wagered.

Here, zero-knowledge proofs can prove a game paid out a specific amount over a period without revealing spins or player identities. However, someone must verify the proof, necessitating either self-verification by gaming operators, which is questionable, or costly audits by regulators.

The optimal solution is a public decentralized network verifying proofs quickly and affordably, allowing users to trust the decentralized protocol instead of a centralized entity.

AI Output and Trustworthiness

The potential for AI deception is well-known. However, there are ways to harness AI’s creativity while ensuring trust in its outputs. With AI’s growing prevalence, it’s vital to confirm that the models we depend on are legitimate, else we risk altering narrative history.

Enter zero-knowledge machine learning (ZKML). This method avoids potential pitfalls, allowing web2 projects uninterested in on-chain solutions to benefit as well.

For example, the University of Southern California collaborated with the Shoah Foundation to create IWitness, enabling users to engage with holograms of Holocaust survivors. This powerful application of machine learning makes it essential for the algorithm producing the hologram to deliver factual information.

ZKPs can implement a “proof of algorithm output,” allowing users to verify that responses stem from a natural language processing algorithm trained accurately on historical data without disclosing underlying datasets.

Users might trust institutions like USC to verify proofs in sensitive cases, but in broader AI applications, relying on centralized entities for proof generation and verification can be problematic. Decentralized proof verification serves better to prevent the construction of false proofs.

Zero-Knowledge as a Trustless, Decentralized Solution

We don’t need to rely solely on companies or technologies to deliver truths when zero-knowledge is here. Several industries can benefit from zero-knowledge blockchain solutions without needing to understand web3 intricacies.

By leveraging ZK proof verification, organizations can maintain their existing infrastructures by creating simple proof systems and utilizing decentralized platforms like zkVerify for proof verification. Users can engage without concerns regarding blockchain integration.

The future of ZK is vast, and organizations need not drastically change operations to gain rewards; they can simply integrate their systems.

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John Camardo
John Camardo is the head of product management at Horizen Labs, focusing on applying zero-knowledge cryptography to solve real-world problems. He leads the zkVerify product, a chain-agnostic blockchain dedicated to verifying ZK proofs efficiently.