Understanding Multi-Party Computation as-a-Service
Blockchain technology is known for its transparency and decentralization, which ensures that all transactions are recorded in publicly available distributed ledgers.
However, this transparency poses a challenge to data privacy.
Since transactional data is accessible to the public, it becomes possible for malicious actors to identify patterns and track individuals.
Addressing Interoperability and Scalability
In addition, the DeFi ecosystem has experienced significant growth, with the emergence of numerous dApps and DeFi protocols on different blockchain networks.
While layer-2 solutions aim to address interoperability and scalability, privacy concerns within the blockchain ecosystem remain unattended.
To tackle this issue while maintaining the fundamental features of blockchain, next-generation projects have started exploring the concept of multi-party computation (MPC) to enhance privacy for data used in blockchain services.
MPC involves distributing computation operations across multiple parties, ensuring that no individual entity can access the data of others and thereby ensuring end-to-end data privacy.
A Solution for Privacy in dApps and DeFi Protocols
However, MPC alone is not sufficient.
To make it valuable for the blockchain ecosystem, it is necessary to integrate MPC with the inherent features of blockchain technology.
Only a few companies have successfully merged MPC with blockchain technology, delivering the desired attributes of both ecosystems to consumers 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.
Like the software-as-a-service (SaaS) model, MPC-as-a-Service allows users to rent services by paying a specific fee to the service provider.
This model allows businesses and individuals to scale their operations as needed through various pay-as-you-use models.