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

In the field of encryption, fully homomorphic encryption ( FHE ), zero-knowledge proof ( ZK ), and multi-party computation ( MPC ) are three advanced technologies that have garnered significant attention. Although they all aim to protect data privacy and security, there are significant differences in their specific application scenarios and technical characteristics. This article will provide an in-depth comparison of these three technologies to help readers better understand their unique features.

Zero-Knowledge Proof ( ZK ): Proving without Revealing

The core of zero-knowledge proof technology lies in how to verify the authenticity of a statement without revealing any specific information. This technology is built on a solid foundation of encryption.

For example, in the case of renting a car, suppose Alice wants to prove to the rental company employee Bob that her credit status is good, but she does not want to provide detailed bank statements. In this case, the "credit score" provided by the bank or payment software can be seen as a form of zero-knowledge proof. Alice can prove that her credit score meets the standards without disclosing any account details.

In blockchain applications, a typical case of ZK technology is anonymous coins. When users make transfers, they need to maintain anonymity while proving that they have enough coins to conduct the transaction ( to prevent double spending ). By generating ZK proofs, miners can verify the legitimacy of transactions and put them on the chain without knowing the identity of the transactors.

Multi-Party Secure Computation ( MPC ): Collaborative computing without disclosure

Multi-party secure computation technology aims to solve how multiple participants can safely perform joint computations without disclosing sensitive information.

A classic application scenario of MPC is: Alice, Bob, and Carol want to calculate their average salary, but they do not want to disclose their specific salaries to each other. MPC allows them to perform complex mathematical operations to ultimately derive the average without revealing any individual's salary information.

In the field of cryptocurrency, MPC technology is widely used for wallet security. Some trading platforms have launched MPC wallets that distribute private keys across multiple locations such as user phones, the cloud, and exchanges. This approach not only enhances security but also improves the recoverability of private keys. Even if a user loses their phone, they can still reconstruct the private key using other parts.

Fully Homomorphic Encryption ( FHE ): Computation under Encryption

The problem addressed by fully homomorphic encryption technology is: how to encrypt sensitive data so that a third party can perform computations on it without decrypting it, while the computation results can still be correctly decrypted by the original data owner.

A typical application scenario of FHE is the processing of sensitive data in cloud computing environments. For example, medical institutions can upload encrypted medical record data to cloud servers, which can perform data analysis without decrypting the data, and finally return the encrypted analysis results to the medical institutions. This not only protects patient privacy but also complies with relevant regulatory requirements.

In the field of blockchain, FHE technology can be used to solve some problems in PoS( proof of stake) networks. For example, in some small PoS networks, nodes may tend to simply follow the validation results of large nodes rather than independently verify each transaction. By applying FHE technology, nodes can complete block validation without knowing the answers of other nodes, thereby enhancing the decentralization of the network.

Comparison of Technical Complexity

There are also differences in implementation difficulty among these three technologies:

• Although ZK is theoretically powerful, designing effective and easily implementable protocols often requires a deep foundation in mathematics and programming.
• MPC needs to solve issues such as multi-party coordination and communication efficiency in practical applications, especially when there are many participants, the costs can be very high.
• Although the concept of FHE is attractive, its complex encryption algorithms result in lower computational efficiency in practical applications, which remains its main bottleneck.

Conclusion

As the degree of digitalization deepens, the challenges facing data security and personal privacy protection are becoming increasingly severe. The three advanced encryption technologies, ZK, MPC, and FHE, provide us with powerful tools to tackle these challenges. Each plays an important role in different scenarios, collectively building a security defense line for the digital world.