The underlying principles of zero-knowledge proofs may be complex, but the technique holds promise for the future of a decentralized web and greater privacy control.
Decentralization is getting lots of airtime. It’s cited as a cornerstone of next-generation technologies, promising increased resilience, reduced points of failure, and democratization of data access. But before we get excited about a shiny new thing, one critical challenge is ensuring data privacy in an ecosystem where control isn’t centralized. It’s not impossible; it’s simply a shift in how we think about this kind of control.
Zero-knowledge proofs (ZKPs), a cryptographic concept, offer an interesting solution. Coupled with the rise of Web3 — a new paradigm for decentralized internet applications —ZKPs stand at the forefront of blending transparency with privacy. Anyone vested in the future of online interactions must understand the potential of ZKPs. Here’s an overview.
What are zero-knowledge proofs?
ZPKs are cryptographic methods involving two parties: the prover and the verifier. One party (the prover) proves to another party (the verifier) that a specific statement is true. What makes these different from other verification methods is that the prover doesn’t have to reveal any information beyond the statement’s validity — credentials for access controls, for example.
The concept of zero-knowledge can be counterintuitive. It means that someone could prove they know something without showing or revealing what that something is. Seems impossible.
What does this look like in real life? Let’s simplify our example. Suppose you solved a very complicated puzzle and want to prove to your friend that you’ve solved it. Your friend doesn’t believe you. The problem is that your friend also wants to solve the puzzle, so you can’t just reveal the solution. However, your friend doesn’t believe you’ve solved it. What can you do?
Properties of zero-knowledge proofs
Zero-knowledge proof protocols have a certain set of criteria to follow:
- Completeness: If the statement is true and the prover and verifier follow the protocol, the verifier can be convinced that the statement is true.
- Soundness: If the statement is false, there’s no way for anyone to be dishonest about it.
- Zero-knowledge: The verifier will learn nothing except that the statement is true.
If you could employ the concept of zero-knowledge proof to this everyday problem, it might look something like this:
Commitment: First, you “commit to your solution. This might involve creating a hash of the solution or encrypting it in a manner that doesn’t disclose the actual answer but does produce a unique result for every potential answer.
- Challenge: Your friend issues a challenge, asking for specific information about your solution that would be extremely difficult, if not impossible, to prove if you hadn’t actually solved the puzzle.
- Response: You provide the required proof based on the challenge. It could involve showing some of your work or providing part of the hash. Maybe your friend checks to see if the provided section aligns with the puzzle without seeing the entire solution.
- Verification: Your fired verifies the proof you’ve presented. If it holds up to scrutiny, your friend can reasonably believe you’ve solved the puzzle without getting the actual solution.
This process can be repeated multiple times with different challenges, increasing the confidence your friend has that you’ve solved the puzzle.
The process became more efficient with the arrival of non-interactive proofs — in which parties only need to interact once through a shared key. These are the two types of zero-knowledge proofs:
- ZK-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge): These are proofs that are both short (succinct) and non-interactive. They require both parties to trust the participants in the process.
- ZK-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge): These rely on publicly verifiable randomness, making them more transparent. These also work with non-trusted setups and are faster than ZK-SNARKS when the witness size is larger.
See also: Cybersecurity Will Shift in 2023 Thanks to AI
What are the challenges in implementing ZPK?
Zero-knowledge proofs (ZKPs) offer a powerful tool for preserving privacy in various applications but implementing them in real-world systems is incredibly challenging for most organizations. Here are some of the primary challenges organizations might face when trying to implement ZKPs:
- Complexity of Cryptography: ZKPs involve intricate cryptographic principles that can be hard for non-experts to grasp. Implementing them requires specialized knowledge, and a lack of expertise can lead to incorrect or vulnerable deployments. Many organizations don’t have the type of cybersecurity expertise in-house to deploy these measures.
- Computational Overhead: Historically, some ZKP protocols have been computationally intensive, leading to higher processing times. Although advancements like zk-SNARKs have reduced computational loads, a significant computational cost is still associated with generating and verifying proofs, especially compared to more straightforward cryptographic methods.
- Integration with Existing Systems: For organizations with established IT infrastructures, integrating ZKPs can be extremely difficult. It often requires re-architecting parts of the system or developing new components to handle ZKP functionalities. Legacy systems are already challenging to integrate, and technology investments are too great to risk a move like this.
- Standardization and Interoperability: The field of ZKPs is evolving, and many different protocols and techniques exist. A lack of standardization can make it tricky for organizations to choose the right approach and ensure interoperability with other systems.
- Tooling and Infrastructure: While there is growing support for ZKPs in various software libraries and platforms, comprehensive tools and mature infrastructure tailored to specific industry needs are still largely in development.
- Auditability and Transparency: While ZKPs protect user privacy, they might make auditing or verifying data challenging for external parties. This leads to potential trust issues in sectors where transparency is critical.
- Cost Implications: The initial investment required for research, development, and implementation of ZKPs can be significant. This can be a barrier for smaller organizations or projects with limited budgets.
Despite these challenges, the potential benefits of ZKPs in enhancing privacy and security are driving many organizations to explore and adopt this technology. For example, some evidence suggests that zero-knowledge-proof protocols may be key to solving scalability issues in areas like blockchain. It could also help companies with interoperability challenges by facilitating private verification across networks, and it may be a more secure way to remain in compliance with privacy regulations.
In one real-life example, The Bank of Israel and VMWare tested zero-knowledge proof technology to protect privacy during central bank digital currency transactions. And zero-knowledge proofs were certainly on Gartner’s 2022 Digital Identity Hype Cycle.
Understanding where ZKPs fit into the bigger picture
The underlying principles of zero-knowledge proofs may be complex, but the technique holds promise for the future of a decentralized web and greater privacy control. But remember, the theoretical elegance of ZKPs only paints half the picture. To truly grasp their transformative potential, one must witness them in action.
How Zero-Knowledge Proofs Might Impact Emerging Cybersecurity Trends
In part 1, we talked about what zero-knowledge proof is and how it might hold the answer to a complex question: How do we balance privacy with security in a decentralized web world? But the beauty of these algorithms is only one part of the answer. Let’s look at the other part: how it might play out in the real world if companies can get a handle on implementing these protocols effectively.
Applications in cybersecurity
ZKPs are computationally intensive, and the integration of ZKP systems can be complex. However, as computational power grows and cryptographic techniques improve, the applicability and use of ZKPs in cybersecurity and privacy are expected to increase.
- Authentication: ZKPs can be used for password-less authentication. Instead of sending a password to a server, users can prove they know the password without revealing it.
- Blockchain and Cryptocurrencies: Privacy coins like Zcash use ZKPs to validate transactions without revealing the specifics of the transaction (like the sender, recipient, or amount).
- Secure Voting: Voters can prove they are eligible to vote without revealing their identities.
- Data Privacy: Users can prove they possess certain data or meet specific criteria without showing the actual data.
What might this look like in the real world?
Here are some interesting potential use cases
Digital identity verification
Traditional verification methods often require users to share personal information. This is a no-go in an increasingly connected world — and one with increasingly privacy-savvy consumers. The challenge organizations have is affirming a user’s identity while minimizing the exposure of personal details.
ZKPs could make it possible to validate the authenticity of a user’s claim without viewing the underlying data. Instead of showing an ID card or requiring users to enter a full birthdate, a ZKP protocol could verify information such as age without revealing an exact birthdate.
Private financial transactions
Digital finance also has a privacy challenge. Cryptocurrency emerged as a way to increase privacy but came under fire for lack of transparency. Traditional banking transactions, too, often involve third parties that have access to transaction details. Truly private financial transactions are a rarity.
ZKPs can validate a transaction’s specifics without revealing specifics to validating parties or the public. This helps reduce fraud and illicit activities. It could prove that a sender has sufficient funds, for example, or that the transaction follows protocol and regulatory rules. However, traditional and cryptocurrencies have explored ZKPs to enhance privacy while remaining compliant with financial regulations.
The evolution of Web3
Web3 heralds the next phase of the internet’s evolution, where decentralized protocols and technologies are predominant. With an emphasis on peer-to-peer interactions, Web3 is changing how users interact with online platforms. As more consumers expect control over their own data, this could mean less reliance on central entities.
If Web3 comes to fruition, ZKPs could play a crucial role. Decentralized apps on Web3 want to function without intermediaries—enter zero-knowledge proofs. They could serve as a bridge between transparency and privacy in a decentralized web world.
A prime example of ZKPs in the Web3 context is their application in Decentralized Finance (DeFi) platforms. DeFi projects often involve lending, borrowing, or swapping assets peer-to-peer. Platforms like Aztec, which integrates ZKPs, allow users to trade or transact on Ethereum in complete privacy. The proofs ensure that while the broader network can verify the legitimacy of a transaction, the specifics — like amounts and involved parties — remain confidential.
Data security in healthcare
Healthcare presents a significant conundrum. Patients’ medical records, treatment plans, and other sensitive information must be accessible to authorized personnel and shielded from unauthorized access or breaches. Traditional methods have often involved centralized databases, which, despite stringent security measures, remain vulnerable to attacks or unauthorized access.
Zero-knowledge proofs present an innovative solution to the puzzle of data access and privacy in healthcare. By utilizing ZKPs, healthcare systems can validate a professional’s right to access specific data or verify a patient’s claim (like insurance eligibility) without exposing the intimate details of medical records or personal information. For example, in hospital settings, ZKPs can facilitate scenarios where medical professionals verify a patient’s eligibility for specific treatments, insurance, or clinical trials. For instance, a system employing ZKPs could validate that a patient meets the criteria for a clinical trial based on age, medical history, or other factors without revealing the patient’s entire health profile.
Secure voting systems
As the world transitions to digital platforms for various electoral processes, ensuring that a vote is both authentic and anonymous is a serious challenge. By doing just that, ZKPs can provide a foundational layer to digital voting systems. Additionally, the system could prove that the vote is counted correctly without showcasing specific voter choices.
It isn’t just major elections. This also has applications in areas such as shareholder votes. The principle remains the same: authenticate the voter and validate the vote without exposing the voter’s choices or personal information.
Digital identity verification
We hinted at this in several of the above sections, but it’s worth mentioning by itself. Proving identity electronically is vital in today’s digital age, but doing so without exposing personal information is critical. This has applications in online shopping, authorizing new services, and even in digital passport systems. This process could safeguard personal information — reducing the risk of harm during data breaches — while enabling online activities safely and securely.
A look forward
We’ve looked at a wide range of real-life applications of zero-knowledge proofs. We could see ZKPs become not just theoretical constructs but practical tools to help companies tackle real-world challenges in decentralization and privacy.
It’s important to remember that while these hold promise, new challenges will arise. We have yet to see widespread adoption, but only time will tell whether these protocols will offer the right equilibrium between validation and privacy. However, in a world where trust is both a commodity and a vulnerability, ZKPs demonstrate that sometimes, believing doesn’t always mean seeing.
