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

We previously discussed the working principle of fully homomorphic encryption ( FHE ). However, many people still confuse FHE with zero-knowledge proofs ( ZK ) and secure multi-party computation ( MPC ), these encryption technologies. Therefore, this article will provide a detailed comparison of these three technologies:

1. Zero-Knowledge Proof ( ZK ): Proving without revealing

The problem that zero-knowledge proof technology solves is: how to verify the authenticity of information without revealing any specific content.

ZK is based on encryption principles, allowing one party to prove to another that they know a certain secret without revealing any information about the secret itself.

For example, Alice can prove her good credit to the car rental employee Bob without having to show specific bank account statements. The "credit score" of payment software is similar to a type of zero-knowledge proof.

In the field of blockchain, the anonymous coin Zcash utilizes ZK technology. When Alice makes a transfer, she can generate a ZK proof that ensures both anonymity and proves that she has the authority to transfer these coins. Miner Bob, after verifying this proof, can add the transaction to the blockchain without knowing Alice's identity.

2. Multi-Party Secure Computation ( MPC ): Joint computation without disclosure

Multi-party secure computation technology is mainly used for: allowing multiple participants to securely compute together without disclosing sensitive information.

MPC allows multiple participants ( such as Alice, Bob, and Carol ) to collaboratively complete a computational task without any party revealing their input data.

For example, Alice, Bob, and Carol want to calculate their average salary without revealing their specific salaries. They can divide their salaries into three parts and exchange two parts with the other two people. Each person sums the numbers they receive and then shares the sum result. Finally, the three of them sum these three results to get the average, but they cannot determine each other's exact salaries.

In the field of cryptocurrency, MPC wallets use this technology. Some trading platforms have launched MPC wallets that divide the private key into multiple parts, which are jointly stored by the user's mobile phone, the cloud, and the platform. Even if the user loses their phone, they can restore the private key through the cloud and the platform.

3. Fully Homomorphic encryption(FHE): Computation can still be performed after encryption

The problem solved by fully homomorphic encryption technology is: how to encrypt sensitive data so that it can be given to untrusted third parties for auxiliary computation, while the results can still be decrypted by us.

FHE allows computations to be performed directly on encrypted data without the need for decryption first. This enables data owners to hand over encrypted data to third parties for processing without worrying about data leakage.

For example, Alice needs to use Bob's powerful computing power for calculations, but does not want Bob to know the real data. She can encrypt the original data ( and add noise ), allowing Bob to process the encrypted data. In the end, Alice decrypts it herself to obtain the real result, while Bob knows nothing about the content.

In the blockchain field, FHE can be used to enhance the security of PoS networks and voting systems. For example, Mind Network utilizes FHE technology to allow PoS nodes to complete block verification without knowing each other's answers, preventing nodes from plagiarizing each other. In voting, FHE can prevent voters from influencing each other, avoiding bandwagon voting.

Summary

ZK, MPC, and FHE are advanced encryption technologies designed to protect data privacy and security, but they differ in application scenarios and technical complexity.

• ZK emphasizes "how to prove", applicable to scenarios that require verification of permissions or identity.
• MPC emphasizes "how to compute", suitable for scenarios where multiple parties need to collaborate on data while protecting their respective privacy.
• FHE emphasizes "how to encryption", applicable to scenarios that require complex computations while keeping the data in an encrypted state.

These three technologies each have their unique challenges in implementation, but they are crucial for protecting our data security and personal privacy. With the continuous development of technology, it is believed that they will play an important role in more fields.