FHE, ZK and MPC: A Comparative Analysis of Three Encryption Technologies

In today's digital age, encryption technology is crucial for protecting data security and personal privacy. This article will delve into three advanced encryption technologies: Fully Homomorphic Encryption (FHE), Zero-Knowledge Proofs (ZK), and Multi-Party Computation (MPC), analyzing their mechanisms, application scenarios, and potential in the blockchain field.

Zero-Knowledge Proof (ZK): Proving without Disclosing

Zero-knowledge proof technology aims to solve the problem of how to verify the authenticity of information without revealing specific content. It is based on encryption principles, allowing one party to prove the existence of a secret to another party without disclosing any substantial information about that secret.

For example, suppose someone needs to prove to a car rental company that their credit status is good, but they do not want to provide detailed bank statements. In this case, a credit scoring system can serve as a form of zero-knowledge proof, proving credit status without disclosing specific financial information.

In blockchain applications, ZK technology can be used to protect transaction privacy. For example, certain anonymous encryption currencies allow users to complete transfers without revealing their identity, while still proving they have sufficient balance, effectively preventing double spending issues.

Multi-Party Computation (MPC): Joint Computing without Disclosure

Multi-party secure computation technology is mainly used to solve how to perform calculations among multiple participants without revealing their respective sensitive information. This technology enables multiple participants to collaborate on computational tasks, but each participant does not need to disclose their input data to others.

A typical application scenario is calculating the average salary of multiple people. Participants can decentralize their salary data, exchange some information, and finally arrive at the average value through aggregation, but throughout the process, no one can know the specific salary amounts of others.

In the cryptocurrency field, MPC technology is used to develop secure multi-signature wallets. This type of wallet disperses the storage of private keys, enhancing the security of funds while also simplifying the user's key management process.

Fully Homomorphic Encryption (FHE): Outsourcing Encrypted Computation

Homomorphic encryption technology addresses the problem of how to perform computations while keeping data in an encrypted state. It allows for the processing of encrypted data without needing to decrypt it first. This means that sensitive data can be safely handed over to a third party for computation, while the computation results can still be correctly decrypted by the data owner.

FHE has a wide range of application prospects in the fields of cloud computing and artificial intelligence. For example, medical institutions can hand over encrypted patient data to cloud service providers for analysis without worrying about data privacy breaches.

In the blockchain field, FHE technology can be used to improve the degree of decentralization of PoS (Proof of Stake) networks. By using FHE, it can prevent verification nodes from plagiarizing each other's validation results, thereby encouraging each node to independently perform calculations and validations.

In addition, FHE can also be applied to decentralized voting systems, ensuring the fairness and privacy of the voting process, and preventing the phenomenon of bandwagon voting.

Technical Comparison

Although these three technologies are dedicated to protecting data privacy and security, there are differences in their application scenarios and technical complexity:

1. Application Focus:

   • ZK focuses on how to prove
   • MPC focuses on how to compute together
   • FHE focuses on how to encryption to support outsourced computation

2. Technical Complexity:

   • The implementation of ZK requires a solid foundation in mathematics and programming.
   • MPC faces synchronization and communication efficiency issues during multi-party collaboration.
   • Although FHE is theoretically attractive, the computational complexity in practical applications remains a significant challenge.

The development and application of these encryption technologies are crucial for protecting data security and personal privacy in our daily lives. With the continuous advancement of technology, we can expect to see more innovative privacy protection solutions being implemented in various fields.