Multi-Party Computation (MPC) vs. Zero-Knowledge Proofs (ZKPs): Which is the Future of Blockchain Privacy?

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As many industries begin to adopt blockchain privacy solutions at high rates due to its innovation in data storage, fintech, and DeFi, they have had to contend with the disadvantages that this technology brings. Multi-Party Computation (MPC) blockchain technology has been seen to transform industries and how we interact with data, but many people are still concerned about the level of privacy offered by these technologies. Although public blockchains offer some privacy in safeguarding data, there is a flip side to it—the exposure of transaction information that can lead to compromises in privacy, raising the challenges of confidentiality in financial dealings. This results in increased pressure for companies to find solutions to the privacy issue without losing decentralization.

This and many more concerns have given rise to decentralized cryptographic protocols such as Multi-Party Computation (MPC) blockchain and Zero-Knowledge Proofs (ZKPs) privacy solutions, both of which have different ways of protecting user identity. The debate of MPC vs ZKP security continues as each offers unique advantages in enhancing blockchain privacy while maintaining decentralization.

As quoted on Twitter in 2022, “In the longer-term future, ZKPs and similar technologies will be critical to blockchain scalability and privacy,” explains Vitalik Buterin, co-founder of Ethereum, stressing his views regarding the public blockchains and privacy. ZKPs are regarded as a decentralization friendly privacy solution. Edward Snowden, who is a known advocate for more privacy on the internet, commented, “When you think about Bitcoin having a public ledger… it’s really just private to the public, but it’s public to the prominent.” These statements reflect his concerns about the inherent transparency of public ledgers and the need for privacy-enhancing technologies like Zero-Knowledge Proofs (ZKPs) and Multi-Party Computation(MPC) to achieve true decentralization.

This article explores MPC and ZKPs in depth, comparing their strengths, limitations, future potential and how they fare in the long run. We will analyze their real-world applications, technical complexities, and the key debates surrounding their adoption in decentralized systems. Which technology will define the future of blockchain privacy? Could a hybrid approach that integrates both MPC and ZKPs be the ultimate solution? Let’s dive in.

What is Multi-Party Computation (MPC)?

Multi-Party Computation (MPC) is a cryptographic technique that allows multiple people (or computers) to work together to calculate a result without revealing their individual data to each other. Suppose you have a group of people each with a piece of secret information like employee salaries for example, and each employee wants to know the average salaries for the team but do not want to reveal their individual earnings, instead of showing their salaries to each other or to a central authority, MPC allows them to work together using cryptographic techniques to compute the result (the average salary) while keeping each person’s input private.

The computation happens in a way that no single party ever sees the full data, and each person holds only a hidden or encrypted version of the data. This allows a protocol to compute the final result securely, and after the computation is done, the group can then see the final result, in this case, the average salary. Nobody learns anything extra about the individual salaries.

How MPC Enables Private Computation Among Multiple Participants

Each individual within the network is split into multiple encrypted shares that are then distributed among a group, ensuring that no single participant has enough information to reconstruct another’s data. They can, however, compute the desired result securely. Most encryption methods protect data when it is stored, e.g. when passwords are saved in a database or when it is sent over a network, like the encrypted messages in WhatsApp. Traditional encryption does not allow computations on encrypted data, meaning if you want to process encrypted data, you usually need to decrypt it first, and this exposes it to potential attackers. With MPC, data remains encrypted even during computation, ensuring privacy at every stage and not just when stored or transmitted.

For example, in a financial setting, banks can use MPC to calculate fraud risk scores from multiple institutions without exposing individual customer data. This privacy-preserving approach makes MPC ideal for applications like decentralized finance (DeFi), secure voting, and confidential business analytics.

Real-World Use Cases of MPC in Blockchain

Secure Key Management: MPC eliminates single points of failure by distributing cryptographic key control across multiple parties. For example, projects like Fireblocks and ZenGo use MPC for secure wallet management.
Confidential Transactions: MPC can facilitate privacy-preserving smart contracts, allowing multiple parties to interact on a blockchain without exposing sensitive information.
Decentralized Finance (DeFi): Protocols can use MPC to enable private order matching and trading strategies without leaking data.

What are Zero-Knowledge Proofs (ZKPs)?

Zero Knowledge Proofs (ZKPs) enable parties (prover or verifier) to carry out cryptographic transactions where one of them, i.e. the prover, is able to prove that a specific statement is true without revealing any underlying information. With ZKP, the legitimacy of the claim can be proven without compromising sensitive data and information.

In this instance, ZKPs allow confidential details of the user identities or accounts to remain hidden while allowing the users to prove their ownership and identity and execute transactions. For ZKPs, maintaining a level of privacy and anonymity is crucial for beating hostile actors wanting to steal data from users. A user can prove they have sufficient funds without disclosing their account balance; they can also facilitate anonymous voting, private smart contracts, and secure authentication in decentralized applications.

Different Types of ZKPs

ZK-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge): Efficient and widely used in privacy-focused blockchains like Zcash.
ZK-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge): Provide enhanced scalability and transparency by removing the need for a trusted setup, making them attractive for applications like StarkWare.

Applications of ZKPs in Blockchain

Private Transactions: Blockchains like Zcash and Aztec use ZKPs to enable anonymous transactions.
Identity Verification: Projects like Polygon ID leverage ZKPs to provide decentralized identity verification without exposing personal information.
Scalability Solutions: Ethereum Layer 2 solutions like zkSync use ZK rollups to enhance transaction throughput while maintaining security.

Key Differences Between MPC and ZKPs

Feature	Multi-Party Computation (MPC)	Zero-Knowledge Proofs (ZKPs)
Computational Efficiency	Requires multiple rounds of interaction	More efficient with batch processing (e.g., ZK rollups)
Scalability	Limited scalability due to communication overhead	Highly scalable, especially with ZK rollups
Security Model	Requires honest majority assumptions	Typically trustless but may require trusted setups
Best Use Cases	Secure multi-party key management, collaborative data analysis	Anonymous transactions, scalable privacy solutions

Challenges and Limitations

MPC: Requires multiple rounds of computation, making it slower for large-scale applications.
ZKPs: Some implementations, like ZK-SNARKs, require a trusted setup, which can introduce security risks.

Potential Regulatory Concerns

According to Jake Chervinsky, General Counsel at Variant Fund, “Privacy tech is under attack. If we don’t advocate for responsible privacy in crypto, regulators will make decisions for us.“

While Privacy-enhancing technologies (PETs), such as Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs) can protect individual privacy by enabling secure data processing and verification without revealing sensitive information, they also present challenges for regulatory frameworks. These technologies can be exploited for illicit activities like money laundering, terrorism financing, and other cybercrimes, necessitating a need to shield against these types of crimes.

PETs and the inherent anonymity they provide tend to complicate the enforcement of financial regulations and anti-money laundering(AML) measures because of the use of anonymous transactions with virtual assets. This has raised concerns in cybersecurity and financial regulation because it has made it difficult for authorities to track and trace illicit financial flows. In response to these concerns, governments and regulatory bodies are exploring strategies to balance the benefits of privacy with the necessity for oversight, developing policies that ensure transparency in the use of surveillance technologies and maintaining logs and records to facilitate meaningful oversight to foster procedural fairness.

In summary, while PETs offer significant advancements in protecting individual privacy, they also pose regulatory challenges that require a delicate balance between safeguarding personal data and ensuring compliance with laws designed to prevent illicit activities.

Which Will Dominate the Future of Blockchain Privacy?

Both Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs) will play vital roles in the evolution of blockchain privacy, but their dominance depends on the specific use cases they serve. ZKPs are more scalable and efficient, making them ideal for privacy-preserving transactions, identity verification, and Layer 2 solutions. On the other hand, MPC excels in collaborative security, such as secure key management and multi-party computations, where trust minimization is essential.

While ZKPs are gaining widespread adoption in privacy-focused blockchains and scalability solutions, MPC remains crucial for enterprise and institutional applications. A hybrid approach that integrates both technologies could provide the most robust privacy solutions for blockchain ecosystems, balancing efficiency, security, and decentralization.

Hybrid Approaches: Can Both Be Used Together?

Some projects, like Secret Network, are exploring combining Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs) for enhanced privacy. This hybrid approach could unlock new use cases by leveraging the strengths of both cryptographic methods—MPC for secure multi-party collaboration and ZKPs for efficient, trustless verification.

How MPC and ZKPs Complement Each Other

Enhanced Privacy & Security: MPC ensures that multiple parties can jointly compute a function without revealing their private inputs, while ZKPs allow proving the correctness of computations without exposing data. Together, they offer stronger privacy guarantees in decentralized applications.
Scalability & Efficiency: ZKPs, especially ZK-rollups, improve computational efficiency by reducing the on-chain verification cost, while MPC distributes processing power among multiple parties, reducing reliance on a single entity.
Trust Minimization: MPC reduces the need for centralized intermediaries by distributing control, while ZKPs ensure that verification can be done without relying on trusted third parties.

The Evolving Landscape of Blockchain Privacy

As blockchain privacy gains importance, both MPC and ZKPs will play critical roles in securing decentralized ecosystems. While ZKPs offer greater efficiency and scalability, MPC provides powerful collaborative security solutions that enable secure multi-party interactions without exposing sensitive data.

The adoption of these privacy-enhancing technologies will be key to driving mainstream adoption of blockchain, particularly in DeFi, identity management, enterprise applications, and institutional finance. Regulators and policymakers will also play a vital role in shaping the future of privacy in blockchain, ensuring that innovations comply with legal frameworks while preserving user confidentiality.

Furthermore, hybrid approaches that combine MPC and ZKPs are emerging, unlocking new possibilities for privacy-preserving applications. Developers, users, and regulators must stay informed on these evolving technologies to ensure a future where privacy and security coexist harmoniously in blockchain applications. As industry leaders continue to push the boundaries of cryptographic research, the next generation of decentralized systems could achieve a balance between transparency, efficiency, and privacy, paving the way for a truly secure and scalable blockchain ecosystem.

Disclaimer: This piece is intended solely for informational purposes and should not be considered trading or investment advice. Nothing herein should be construed as financial, legal, or tax advice. Trading or investing in cryptocurrencies carries a considerable risk of financial loss. Always conduct due diligence.

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