What Are Zero-Knowledge Proofs?

Zero-knowledge proofs (ZKPs) allow one party (the prover) to prove the truth of a statement without revealing sensitive data. Proponents of the tech argue that they have tremendous potential in multiple use cases that require privacy, such as financial transactions, electronic voting, and identity verifications, among others. They are already in use to help scale blockchain networks like Polygon without sacrificing decentralization or security.

ZKPs emerged in the 1980s due to the pioneering work of Shafi Goldwasser, Silvio Micali, and Charles Rackoff. Because they are extraordinarily complex and difficult to implement, they remained mostly theoretical for many before they could be improved and better understood. Since then, they have evolved into a highly sophisticated technology.

In this guide, we will explain everything you need to know about zero-knowledge proofs, including their history, use cases, and how they work. From there, we will detail the pros and cons of this innovative cryptographic method and its growing relevance in the cryptocurrency industry.

What Are Zero-Knowledge Proofs?

Zero-Knowledge Proofs (ZKPs) are cryptographic protocols that allow one party to demonstrate to another party that they possess knowledge of certain data without revealing the data itself. In essence, they can be used to prove the accuracy of the information without disclosing additional information.

For instance, a ZKP could verify a person’s identity through official documents without requiring the person to provide a copy of those documents. It could also prove knowledge of the solution to a mathematical puzzle without revealing the solution itself.

This may seem a bit niche on the surface, but they have significant utility across multiple important industries, including the crypto market.

History of ZKPs

The concept of ZKPs was originally presented in 1985 by Shafi Goldwasser, Silvio Micali, and Charles Rackoff in a paper titled “The knowledge complexity of interactive proof-systems.” In the paper, the authors defined zero-knowledge proofs as “those proofs that convey no additional knowledge other than the correctness of the proposition in question.”

The paper demonstrated the possibility of proving knowledge of a secret without revealing the secret itself through interactions between the prover and the verifier. These proofs were dubbed “interactive zero-knowledge proofs” because they required repeated communications between the prover and verifier. The team quickly started work on removing this requirement as they believed that it would be too difficult to scale these proofs otherwise.

Shortly after the first paper, Amos Fiat and Shamir developed a new technique that enabled non-interactive ZKPs. This made the technology vastly more scalable and enabled third parties, outside of the original prover and verifier, to verify the proofs.

In 2011, Succinct Non-Interactive Arguments of Knowledge (SNARKs) were created by cryptographers Nir Bitansky, Ran Canetti, and Alessandro Chiesa. This is a type of ZKPs that offer an efficient and compact way to generate and verify cryptographic proofs. They use advanced mathematical problems involving elliptic curves and bilinear pairings.

Between 2016 and 2018, Scalable Transparent Arguments of Knowledge (STARKs) were developed. STARKs are considered an evolution of existing SNARKs. Unlike his predecessor, they don’t require trust setups, enhancing transparency and operability. As a bonus, they swapped out elliptic curves with hash functions, effectively making them secure from attacks using quantum computers.

How Do Zero-Knowledge Proofs Work?

ZKPs operate through an interactive challenge response between the prover and the verifier. First, the prover generates a cryptographic commitment that conceals the secret data while mathematically linking to it. Today, these commitments typically use cryptographic hash functions, which convert data into a long, fixed string of outputs that are easy to verify but extremely hard to reverse.

Subsequently, the verifier sends a random challenge to the prover, who must respond with a proof demonstrating knowledge of the information without directly revealing it. If the response is correct, the verifier is convinced that the prover possesses the knowledge, even though the information remains secret.

Here is a detailed step-by-step explanation of how ZKPs work:

1. The prover generates a cryptographic commitment that conceals the secret data while mathematically linking to it, often using a hash function.
2. The verifier issues a “challenge,” requesting the prover to demonstrate a certain property of the secret data, such as whether it falls within a specific range.
3. The prover uses the secret data to generate a “response,” satisfying the property requested by the challenge.
4. The verifier validates that the response meets the challenge, without accessing the secret data itself.
5. For interactive ZKPs, steps 2 to 4 are repeated multiple times with random challenges to minimize the risk of deception.
6. After several rounds of interaction, the verifier gains statistical certainty about the validity of the assertion, without the secret data being exposed.

Example of a Zero-Knowledge Proof in Action

ZKPs are commonly used in the banking industry, often for identity verification and transaction settlement. For example, if a customer wants to prove their identity to a bank without revealing sensitive personal data like their social security number, the parties can use a zero-knowledge proof of identity (ZKPI). This allows the customer to provide proof that their identity has been checked without revealing any sensitive information to the bank.

Zero Knowledge vs Zero Trust Explained

The term “zero knowledge” refers specifically to cryptographic proofs that allow verification of information without exposing the underlying data. It enables privacy preservation during validation and authentication processes.

On the other hand, “zero trust” is a broader cybersecurity approach that operates under the assumption that no user or device should inherently be trusted within a system. The zero-trust model requires continuous authentication and authorization for granting access to resources.

The goal of zero trust is to minimize internal threats like data leaks, ransomware infections, and other malicious activities. It casts a wider net of ongoing scrutiny across all interactions.

What Are Zero-Knowledge Proofs Used For?

Several major use cases of ZKPs include:

• Anonymous payments: Cryptocurrencies like Zcash utilize ZKPs to conceal transaction details.
• Decentralized identity systems: ZKPs enable identity verification while preserving user privacy.
• Zero-Knowledge Rollups (ZKRs): ZKPs can act as a foundation for new, scalable Layer 2 blockchain networks.
• Authentication: Users can authenticate their identity without revealing passwords or personal data.
• Electronic voting: Vote counts can be verified without exposing individual votes.
• Result validation: Blockchains like Ethereum can validate off-chain computation results through ZKPs.
• Finance: Institutions can verify private customer data without accessing sensitive or private information.

Why Are Zero-Knowledge Proofs Important in Crypto?

Zero-knowledge proofs have recently become one of the most exciting technologies in the crypto market because they could help solve the blockchain trilemma. The trilemma refers to the difficulty of improving one of the three main aspects of blockchain networks, scalability, decentralization, and security, without harming one or both other aspects.

ZKPs are both fast (and thus scalable) and promote privacy, which is a rarity in the crypto world. They are also easy to verify, which promotes decentralization as well because they make it easier for more regular people to secure the network.

Use Cases of Zero-Knowledge Proofs in Crypto

ZKPs seem to be most useful in the development of Layer 2 networks (L2s), blockchains that sit on top of other, already secure networks to move as many transactions off of the mainchain as possible. This reduces the load on the main network, speeding up transactions and lowering fees.

Developers are using ZKPs to develop Zero-Knowledge Rollups (ZKRs), which can bundle a massive amount of transactions into a single batch to be verified all at once. Naturally, this can vastly reduce the load of verifying all of these transactions, as only a single proof is needed. The complexity of this strategy made it difficult to implement, but projects like Polygon zkEVM and StarkNet have already applied it to create scalable L2s.

Other projects, such as Mina Protocol, use zk-SNARKs to build Layer 1 networks, making them as lightweight as possible. Instead of storing the network’s entire state (including all addresses, amounts, and transaction histories), users can verify every single past block with a single proof.

ZKPs are also already in use by privacy-focused crypto projects like Zcash. They can be used to hide nearly every aspect of a transaction, including sender addresses, recipient addresses, and even transaction amounts. Since developers have only started building this tech recently, there may be many more valuable use cases to explore in the coming years.

Benefits and Limitations of Zero-Knowledge Proofs

Key advantages of ZKPs include improved privacy by concealing sensitive data, enhanced cryptographic security during data verification and authentication, opportunities for previously impossible use cases due to new privacy requirements, and models like STARKs that eliminate the need for third-party trust.

ZKPs are certainly impressive and useful in many different ways, but that doesn’t mean that they don’t have any potential drawbacks. Firstly, they can be incredibly complex and difficult to design, which makes development significantly slower than other concepts like Optimistic Rollups (ORs).

Generating and verifying ZKPs can also be computationally expensive, potentially increasing hardware requirements and costs. Furthermore, auditing and debugging can be more challenging, increasing vulnerability risks.

What Is the Future of Zero-Knowledge Proofs?

Zero-knowledge proofs are among the most significant cryptographic advancements in the 2000s. By enabling validation of knowledge or claims without exposing sensitive data, they have dozens of use cases across many different industries. ZKPs are already taking off in the crypto industry, leading to the creation of multiple innovative blockchains, and seem to be slowly spreading to traditional finance as well.

Cryptographers are still trying to refine and innovate ZKPs to expand their use cases and fix a handful of drawbacks with the tech. With enough time and effort, they could become integral to most industries that require privacy and trust, like banking, healthcare, government services, and data security.

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Julia Sakovich

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I’m a content writer and editor with extensive experience creating high-quality content across a range of industries. Currently, I serve as the Editor-in-Chief at Coinspeaker, where I lead content strategy, oversee editorial workflows, and ensure that every piece meets the highest standards. In this role, I collaborate closely with writers, researchers, and industry experts to deliver content that not only informs and educates but also sparks meaningful discussion around innovation.

Much of my work focuses on blockchain, cryptocurrencies, artificial intelligence, and software development, where I bring together editorial expertise, subject knowledge, and leadership experience to shape meaningful conversations about technology and its real-world impact. I’m particularly passionate about exploring how emerging technologies intersect with business, society, and everyday life. Whether I’m writing about decentralized finance, AI applications, or the latest in software development, my goal is always to make complex subjects accessible, relevant, and valuable to readers.

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