BTC

$98168.575

4.25%

ETH

$3354.043

9.90%

BNB

$625.264

3.60%

XRP

$1.176

8.88%

Glossary

Multi-Party Computation as-a-Service

November 21, 2023 - Around 4 mins mins to read

Blockchain technology has gained recognition for its transparency and decentralization, as all transactions are recorded in publicly available distributed ledgers. However, this very transparency poses a challenge to data privacy. With transactional data accessible to the public, it becomes easier for malicious actors to identify patterns and track individuals.

In recent years, the decentralized finance (DeFi) ecosystem has experienced significant growth, giving rise to various decentralized applications (dApps) and DeFi protocols on different blockchain networks. While layer-2 solutions aim to address concerns related to interoperability and scalability, privacy issues associated with blockchain technology remain largely unresolved.

To tackle these privacy concerns while upholding the fundamental principles of blockchain technology, next-generation projects have begun exploring the concept of Multi-Party Computation (MPC). MPC involves distributing computation operations among multiple parties, ensuring that no single entity can access the data of other parties. This approach guarantees end-to-end data privacy.

However, MPC alone is not sufficient. To make it valuable for the blockchain ecosystem, it needs to be integrated with the inherent features of blockchain technology. By leveraging the transparency, consensus, and integrity provided by blockchain, MPC can be orchestrated without compromising privacy. Currently, only a few companies have successfully merged MPC with blockchain technology, offering the desired attributes of both ecosystems to users and service providers.

Nevertheless, building an MPC solution from scratch requires significant time, effort, and resources. As a result, MPC-as-a-Service has emerged as an innovative solution for enterprises and individuals seeking end-to-end privacy for their blockchain services. Similar to the software-as-a-service (SaaS) model, MPC-as-a-Service allows users to rent the services by paying a specific fee to the service provider. This model offers businesses and individuals the flexibility to scale their operations as needed, with various pay-as-you-use options.

MPC-as-a-Service providers offer a range of features and benefits to their users. One of the key advantages is the ability to securely compute and analyze sensitive data without disclosing it to any single entity. This is particularly crucial for industries that handle sensitive information, such as healthcare, finance, and government. With MPC, these industries can collaborate and share data securely while preserving the privacy of individuals involved.

Additionally, MPC-as-a-Service providers offer robust security measures to protect data during computation. They employ cryptographic protocols and techniques to ensure that data remains confidential and is not compromised by any participating party. These protocols typically involve secure multiparty computation protocols, zero-knowledge proofs, and encryption methods.

Furthermore, MPC-as-a-Service providers often offer customizable solutions to suit the specific requirements of their clients. Users can define the computation tasks they need and specify the privacy constraints, ensuring that the MPC service aligns with their unique business needs.

Let’s consider an example to better understand the potential use cases of MPC-as-a-Service. Imagine a healthcare consortium consisting of multiple hospitals and research institutions. These entities collect and store sensitive patient data for medical research purposes. However, sharing this data poses a significant challenge due to privacy concerns.

By utilizing an MPC-as-a-Service provider, the healthcare consortium can securely compute aggregated statistics or conduct joint analyses on the combined data without any individual entity having access to the raw patient records. This allows researchers to gain insights and perform studies on a larger dataset while maintaining the privacy of patients.

Another use case for MPC-as-a-Service is in financial applications. Traditional financial institutions, such as banks, often need to collaborate on compliance-related activities, such as Know Your Customer (KYC) processes or anti-money laundering (AML) checks. MPC can enable these institutions to securely collaborate on such activities without directly sharing their customer data, reducing the risk of data breaches or unauthorized access.

Overall, Multi-Party Computation as-a-Service offers a promising solution for enhancing data privacy in the blockchain ecosystem. By leveraging the transparency and integrity of blockchain technology while ensuring end-to-end data privacy through MPC, businesses and individuals can securely collaborate, compute, and analyze sensitive data without compromising confidentiality. As more companies integrate MPC with blockchain technology and offer it as a service, we can expect to see greater adoption of this approach and the emergence of new use cases.

About the Author:

Kurt Nielsen, the Co-Founder & President of Partisia Blockchain, is a renowned industry professional specializing in advanced distributed cryptography and decentralized infrastructure. With extensive experience in strategic decision-making, applied information economics, data science, and mechanism design, Kurt has made significant contributions across various industries. He holds a Ph.D. in Economics from the University of Copenhagen and has previously worked as a professor at the same university. Kurt has co-founded several companies, including Partisia, Sepior, Energiauktion.dk, Secata, and Partisia Blockchain.

Avatar of Coincu

Author

Coincu

Glossary

Multi-Party Computation as-a-Service

Blockchain technology has gained recognition for its transparency and decentralization, as all transactions are recorded in publicly available distributed ledgers. However, this very transparency poses a challenge to data privacy. With transactional data accessible to the public, it becomes easier for malicious actors to identify patterns and track individuals.

In recent years, the decentralized finance (DeFi) ecosystem has experienced significant growth, giving rise to various decentralized applications (dApps) and DeFi protocols on different blockchain networks. While layer-2 solutions aim to address concerns related to interoperability and scalability, privacy issues associated with blockchain technology remain largely unresolved.

To tackle these privacy concerns while upholding the fundamental principles of blockchain technology, next-generation projects have begun exploring the concept of Multi-Party Computation (MPC). MPC involves distributing computation operations among multiple parties, ensuring that no single entity can access the data of other parties. This approach guarantees end-to-end data privacy.

However, MPC alone is not sufficient. To make it valuable for the blockchain ecosystem, it needs to be integrated with the inherent features of blockchain technology. By leveraging the transparency, consensus, and integrity provided by blockchain, MPC can be orchestrated without compromising privacy. Currently, only a few companies have successfully merged MPC with blockchain technology, offering the desired attributes of both ecosystems to users and service providers.

Nevertheless, building an MPC solution from scratch requires significant time, effort, and resources. As a result, MPC-as-a-Service has emerged as an innovative solution for enterprises and individuals seeking end-to-end privacy for their blockchain services. Similar to the software-as-a-service (SaaS) model, MPC-as-a-Service allows users to rent the services by paying a specific fee to the service provider. This model offers businesses and individuals the flexibility to scale their operations as needed, with various pay-as-you-use options.

MPC-as-a-Service providers offer a range of features and benefits to their users. One of the key advantages is the ability to securely compute and analyze sensitive data without disclosing it to any single entity. This is particularly crucial for industries that handle sensitive information, such as healthcare, finance, and government. With MPC, these industries can collaborate and share data securely while preserving the privacy of individuals involved.

Additionally, MPC-as-a-Service providers offer robust security measures to protect data during computation. They employ cryptographic protocols and techniques to ensure that data remains confidential and is not compromised by any participating party. These protocols typically involve secure multiparty computation protocols, zero-knowledge proofs, and encryption methods.

Furthermore, MPC-as-a-Service providers often offer customizable solutions to suit the specific requirements of their clients. Users can define the computation tasks they need and specify the privacy constraints, ensuring that the MPC service aligns with their unique business needs.

Let’s consider an example to better understand the potential use cases of MPC-as-a-Service. Imagine a healthcare consortium consisting of multiple hospitals and research institutions. These entities collect and store sensitive patient data for medical research purposes. However, sharing this data poses a significant challenge due to privacy concerns.

By utilizing an MPC-as-a-Service provider, the healthcare consortium can securely compute aggregated statistics or conduct joint analyses on the combined data without any individual entity having access to the raw patient records. This allows researchers to gain insights and perform studies on a larger dataset while maintaining the privacy of patients.

Another use case for MPC-as-a-Service is in financial applications. Traditional financial institutions, such as banks, often need to collaborate on compliance-related activities, such as Know Your Customer (KYC) processes or anti-money laundering (AML) checks. MPC can enable these institutions to securely collaborate on such activities without directly sharing their customer data, reducing the risk of data breaches or unauthorized access.

Overall, Multi-Party Computation as-a-Service offers a promising solution for enhancing data privacy in the blockchain ecosystem. By leveraging the transparency and integrity of blockchain technology while ensuring end-to-end data privacy through MPC, businesses and individuals can securely collaborate, compute, and analyze sensitive data without compromising confidentiality. As more companies integrate MPC with blockchain technology and offer it as a service, we can expect to see greater adoption of this approach and the emergence of new use cases.

About the Author:

Kurt Nielsen, the Co-Founder & President of Partisia Blockchain, is a renowned industry professional specializing in advanced distributed cryptography and decentralized infrastructure. With extensive experience in strategic decision-making, applied information economics, data science, and mechanism design, Kurt has made significant contributions across various industries. He holds a Ph.D. in Economics from the University of Copenhagen and has previously worked as a professor at the same university. Kurt has co-founded several companies, including Partisia, Sepior, Energiauktion.dk, Secata, and Partisia Blockchain.

Leave a Reply