●     MPC

Secure multi-party computation (MPC) was first introduced by A. Yao[1] in 1982 through ‘Yao’s Millionaires’ Problem’ raised. After decades of continuous research, MPC has been greatly developed and achieved fruitful results.

MPC (also known as secure computation, multi-party computation or privacy-preserving computation) is s subfield of cryptography with the goal of creating methods of parties to jointly compute a function over their inputs while keeping those inputs private.

In MPC, a given number of participants, p1, p2, …, pN, each have private data, respectively d1, d2, …, dN. Participants want to compute the value of a public function on that private data: F (d1, d2, …, dN) while keeping their own inputs secret[2]. All that parties can learn is what they can learn from the output and their own input.

Informally speaking, the most basic properties that an MPC protocol aims to ensure contain: 1) input privacy – no information about the private data held by the parties can be inferred from the messages sent during the execution of protocol; the only information that can be inferred about the private data is whatever could be inferred from seeing the output of the function alone; 2) correctness – any proper subset of adversarial colluding parties willing to share information or deviate from the instructions during the protocol execution should not be able to force honest parties to output an incorrect result; this correctness goal comes in two models: either the honest parties are guaranteed to compute the correct output, or they abort if they find an error.

Furthermore, MPC is decentralized in a very real sense based on its protocol. Thus, there is no need of privilege participants or credible third party in MPC-based application. Each participant with data resource has equal right that be secured by MPC protocol. Each data owner has ability to launch the computing task.

●     MPC has a wide range of Application

Secure multi-party computation (MPC) technology has a very wide range of applications with the rapid development of the blockchain and the Internet that data resources and security become important competitiveness. MPC promises to solve the phenomenon of ‘data islands’ that the unfulfilled unified of data for owners and users by ensuring both privacy of data input and correctness of data computation. Moreover, MPC ensures that data input from participating parties is not compromised through protocols without third parties.

Based on its features therefore, MPC can be applied both in classic and emerging areas, e.g., key management system, online voting, electronic bidding, joints signature, and in conjunction with the signcryption techniques, authentication, cryptographic technology.

[1] Andrew C. Yao, Protocols for secure computations (extended abstract) https://research.cs.wisc.edu/areas/sec/yao1982-ocr.pdf

[2] Moti Yung: From Mental Poker to Core Business: Why and How to Deploy Secure Computation Protocols? ACM Conference on Computer and Communications Security 2015: 1-2

About HashKey Me Based on MPC (Multi-Party Computation), HashKey Me is a decentralized identity wallet supporting multiple blockchains. With email addresses as unique identities, users can generate accounts compatible with a number of major blockchain ecosystems, including Cosmos, Bitcoin, Ethereum, Polkadot, Polygon, PlatON, Avalanche, Arbitrum, etc. While safeguarding digital assets in a decentralized manner, the solution also lowers barriers to access, for it does not require managing mnemonic phrases and private keys. Using an email address as an user's unique identity, HashKey Me enables transactions across multiple blockchains, creates (by snapshot) and display NFTs on demand*, and share them on social networks such as Twitter and Telegram with One-click. *Note: the NFT minting function is provided by third-party DApps. Such DApps/websites are maintained by third-party authors and are not affiliated with HashKey Me. HashKey Me is not liable for any third-party DApps. Please ensure that you understand the function for each DApp before interacting and comply with all applicable laws and regulations.

●     MPC

Secure multi-party computation (MPC) was first introduced by A. Yao[1] in 1982 through ‘Yao’s Millionaires’ Problem’ raised. After decades of continuous research, MPC has been greatly developed and achieved fruitful results.

MPC (also known as secure computation, multi-party computation or privacy-preserving computation) is s subfield of cryptography with the goal of creating methods of parties to jointly compute a function over their inputs while keeping those inputs private.

In MPC, a given number of participants, p1, p2, …, pN, each have private data, respectively d1, d2, …, dN. Participants want to compute the value of a public function on that private data: F (d1, d2, …, dN) while keeping their own inputs secret[2]. All that parties can learn is what they can learn from the output and their own input.

Informally speaking, the most basic properties that an MPC protocol aims to ensure contain: 1) input privacy – no information about the private data held by the parties can be inferred from the messages sent during the execution of protocol; the only information that can be inferred about the private data is whatever could be inferred from seeing the output of the function alone; 2) correctness – any proper subset of adversarial colluding parties willing to share information or deviate from the instructions during the protocol execution should not be able to force honest parties to output an incorrect result; this correctness goal comes in two models: either the honest parties are guaranteed to compute the correct output, or they abort if they find an error.

Furthermore, MPC is decentralized in a very real sense based on its protocol. Thus, there is no need of privilege participants or credible third party in MPC-based application. Each participant with data resource has equal right that be secured by MPC protocol. Each data owner has ability to launch the computing task.

●     MPC has a wide range of Application

Secure multi-party computation (MPC) technology has a very wide range of applications with the rapid development of the blockchain and the Internet that data resources and security become important competitiveness. MPC promises to solve the phenomenon of ‘data islands’ that the unfulfilled unified of data for owners and users by ensuring both privacy of data input and correctness of data computation. Moreover, MPC ensures that data input from participating parties is not compromised through protocols without third parties.

Based on its features therefore, MPC can be applied both in classic and emerging areas, e.g., key management system, online voting, electronic bidding, joints signature, and in conjunction with the signcryption techniques, authentication, cryptographic technology.

[1] Andrew C. Yao, Protocols for secure computations (extended abstract) https://research.cs.wisc.edu/areas/sec/yao1982-ocr.pdf

[2] Moti Yung: From Mental Poker to Core Business: Why and How to Deploy Secure Computation Protocols? ACM Conference on Computer and Communications Security 2015: 1-2

About HashKey Me Based on MPC (Multi-Party Computation), HashKey Me is a decentralized identity wallet supporting multiple blockchains. With email addresses as unique identities, users can generate accounts compatible with a number of major blockchain ecosystems, including Cosmos, Bitcoin, Ethereum, Polkadot, Polygon, PlatON, Avalanche, Arbitrum, etc. While safeguarding digital assets in a decentralized manner, the solution also lowers barriers to access, for it does not require managing mnemonic phrases and private keys. Using an email address as an user's unique identity, HashKey Me enables transactions across multiple blockchains, creates (by snapshot) and display NFTs on demand*, and share them on social networks such as Twitter and Telegram with One-click. *Note: the NFT minting function is provided by third-party DApps. Such DApps/websites are maintained by third-party authors and are not affiliated with HashKey Me. HashKey Me is not liable for any third-party DApps. Please ensure that you understand the function for each DApp before interacting and comply with all applicable laws and regulations.