FHE, ZK, and MPC: A Comparison of Three Advanced Encryption Technologies

In today's digital age, data security and privacy protection have become increasingly important. FHE, ZK, and MPC, as three advanced encryption technologies, each provide unique solutions for different application scenarios. This article will provide a detailed comparison of these three technologies to help readers better understand their characteristics and applications.

Zero-Knowledge Proof ( ZK )

Zero-knowledge proof technology addresses the issue of how to verify the authenticity of information without disclosing specific details. It is based on cryptographic principles and allows one party to prove to another that they know a certain secret without revealing any information about that secret.

For example, suppose Alice wants to prove her good credit status to Bob, an employee of a car rental company, but does not wish to provide detailed bank statements. In this case, a "zero-knowledge proof" similar to a credit score can come in handy. Alice can prove that her credit score meets the requirements without showing specific account information.

In the field of blockchain, a typical application of ZK technology is anonymous transactions. For example, certain encryption currency projects allow users to transfer funds while remaining anonymous, and verify the legality of transactions through ZK proofs, effectively preventing double spending.

Multi-Party Secure Computation ( MPC )

Multi-party secure computation technology is mainly used to solve how multiple parties can jointly complete computational tasks without disclosing their respective sensitive information.

For example, Alice, Bob, and Carol want to calculate the average salary among the three of them, but they do not want to disclose the exact amounts to each other. Through MPC technology, they can divide their respective salaries into three parts, exchange some information, and finally calculate the average value through a series of computations without revealing the specific salaries of each individual.

In the cryptocurrency field, MPC technology is applied to develop more secure wallet solutions. Some trading platforms have launched MPC wallets that split private keys into multiple parts, which are stored separately on user devices, in the cloud, and on platform servers. This method not only enhances security but also increases recovery convenience.

Fully Homomorphic Encryption ( FHE )

Fully homomorphic encryption technology is dedicated to solving how to encrypt sensitive data so that it can be processed by untrusted third parties while ensuring that the results can be correctly decrypted.

Suppose Alice needs to utilize Bob's powerful computing capability, but does not want Bob to know the original data. Through FHE, Alice can encrypt the data, allowing Bob to perform computations in the encrypted state, and finally, Alice decrypts to obtain the real result. This method is particularly valuable for processing sensitive information in cloud computing environments.

In the blockchain field, FHE technology can be used to improve the PoS consensus mechanism and voting systems. For example, some projects are exploring the use of FHE technology to allow PoS nodes to complete block validation without knowing each other's answers, or to enable voters to achieve accurate result statistics while keeping their voting intentions confidential. This helps to enhance the decentralization and fairness of the system.

Summary

Although ZK, MPC, and FHE are all intended to protect data privacy and security, they differ in application scenarios and technical complexity:

• ZK focuses on "how to prove", applicable to scenarios that require validation of permissions or identity.
• MPC focuses on "how to compute", suitable for situations where multiple parties need to jointly compute while protecting their own data privacy.
• FHE emphasizes "how to encryption", making it possible to perform complex computations while keeping the data in an encryption state.

In terms of technical complexity, ZK requires deep mathematical and programming skills, MPC faces challenges in synchronization and communication efficiency, while FHE has significant obstacles in computational efficiency.

As the level of digitalization continues to increase, these encryption technologies will play an increasingly important role in protecting our data security and personal privacy. Understanding the characteristics and applications of these technologies will help us better cope with current and future data security challenges.