What Is Multi-Party Computation And How Does It Work? – 2022 Guide

You are likely to know about MPC on the off chance you work in an institutionally advanced resource industry. While MPC has been there since the mid-1980s, it was as of late integrated with the advanced resource market, and from that point forward, MPC has become quite possibly the most well-known technology utilized by wallet suppliers and managers to get crypto resources.

But what precisely is MPC? What are the benefits, and how does it work? We’ll go over all you need to know about the technology and how it’s used in digital asset security today.

To better comprehend MPC’s origins, let’s start with a general introduction to cryptography.

Cryptography Development

Information has long been hidden via cryptography, all the way back to the Greek ruler Histiaeus, who tattooed messages on his slaves’ scalps to prevent enemies from intercepting wartime conversations.

Since then, encryption has progressed to accommodate an increasing number of applications. New cryptographic methods, such as public-key cryptography, have emerged, enabling the contemporary techniques and allowing for ever more complicated data security.

What is Multi-Party Computation (MPC)?

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MPC (multi-party computing) is a cryptographic technology that allows for shared computation while maintaining data confidentiality and privacy. It is a way of distributing computation among numerous individuals in which no single party has access to the knowledge of the others.

MPC improves on traditional cryptographic procedures that favor security and privacy by allowing the parties involved to compute data without the involvement of a third party. Secure multi-party computation, secure computation, and privacy-focused computation are other names for multi-party calculation.

A cryptographic key can be broken down and disseminated using MPC technology, allowing an encrypted database to be accessed only when all key fragment holders get together. The data is inaccessible to any solitary key fragment possessor. And until every key fragment holder is present, nobody can access the data.

MPC’s Background

In 1982, the viability of privacy-focused computation began to make its way into the encryption industry. Cryptographers have hitherto exclusively concentrated on encrypting messages sent between two parties. The MPC engine was launched in 1982 by 2PC (2-party computation).

Andrew Yao introduced 2PC, a program that solves the millionaire’s dilemma by giving cryptographic means for interacting with “true,” “false,” and other “Boolean logic.” For example, he intended to assist two wealthy persons, John and Jane, in determining who is more prosperous. The problem was then completing the calculation without disclosing their personal fortune.

In 1986, Yao put the 2PC approach into practice. In 1987, computer scientists O. Goldreich, A. Wigderson, and Silvio Micali delved into 2PC, taking it a step further by using generalization to include more parties in computation. As a result, the GMW technique was developed, which gave an MPC calculation the capacity to guard against dishonest actors.

MPC gained broader recognition in 1990 when it began to be used for mobile security, universal composability, and other applications.

It wasn’t until 2008 that a functional, secure, and utterly private application was developed. In 2010, the concept was used in digital asset wallets, boosting security. The multi-party computation key-refreshing algorithm’s initial iteration was released in 2019.

MPC Protects Private Keys

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MPC wallets can be used to protect a single piece of sensitive data owned by a single entity, such as the private keys that govern digital assets.

Private keys are typically stored in one location without MPC, either in a hot wallet (connected to the internet) or in cold storage (not linked to the internet) (offline). According to system design language, this produces a “single point of failure,” which is an appealing target for hackers.

Is it safe to use multi-party computing?

Even if a hacker gained access to a single MPC node, they would have no way of knowing the total value of all the nodes’ output. They’d have to execute a simultaneous attack against the total number of devices required to sign a transaction to obtain control of a wallet protected by MPC.

If there are ten nodes and the threshold for signing a transaction is five, attackers would need to break into six of them and take the key shares. Proactive security techniques like key rotation, which automatically moves sensitive private key material between nodes, make this more difficult.

Assuming MPC is implemented on secure hardware, the requirement to attack multiple fronts at once makes MPC far more secure than other private key storage systems with a single point of failure, such as hot and cold wallets.

Additionally, MPC’s flexible governance reduces the likelihood of rogue personnel having access to a wallet and stealing funds.

Multi-party Computation’s Advantages

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Commercially-ready: Secure multi-party computation is no longer a data scientist’s dream; it is a verified reality. Clients are now using Secret Computing® to detect financial fraud better, evaluate the aggregate model features across private datasets, and predict heart disease, among other things.

There are no trusted third parties who have access to the information: It is no longer essential to entrust data security and broker exchanges to a third party. Data is never transferred outside of a client’s internal firewall in an MPC.

Eliminates compromise between data usability and data privacy: There is no need to disguise or eliminate any features to preserve data privacy. Without jeopardizing privacy, any element can be used in an analysis.

GDPR and compliance with national data privacy laws: The multi-party compute solution fulfills and exceeds cross-border data transfer regulations (because the data never moves).

High precision and accuracy: The accuracy and precision of the results meet or surpass the client’s expectations.

Quantum-safe: Because data is divided up and spread across participants (or “secret shared”) during the computation, it is considered encrypted even when in use.

Conclusion

Secure data sharing and secure data storage are two applications for MPC technology. It can be used to share the data analysis process rather than actual data, minimizing the necessity for data sharing in the first place. Developers can also use it to disseminate cryptographic keys. It considerably improves the security of data storage by dividing a key among numerous users.