Data privacy has been one of the biggest technology issues since its beginning. From the early days of the internet to the rise of Web3 development, ensuring the privacy of all data contained in a technology has often been a critical challenge. Every technology we use relies on data to function effectively. However, managing this data securely while maintaining its usability has always been a complicated issue.

In Web3 space, decentralization and transparency are key principles. Due to their nature, it is important for projects to pay attention to the data security of users and transactions. Fully Homomorphic Encryption or FHE for short, provides an innovative solution for web3 projects. This encryption allows data to remain encrypted which ensures complete privacy and security. FHE encryption enables secure data processing without revealing any sensitive information. By using FHE, web3 projects can maintain privacy and security without compromising the functionality of the technology they use.

What is Fully Homomorphic Encryption (FHE)?

Fully Homomorphic Encryption (FHE) is an advanced cryptographic method in blockchain development that allows data to remain encrypted during processing. In traditional encryption methods, data must be decrypted to perform computations or analysis. But in FHE, any sensitive data or information is never exposed. This is an ideal solution for web3 projects that require high levels of data privacy and security.

Why is FHE Important?

In traditional encryption, data is protected during storage and transmission. However, when computations are needed, the data must be decrypted. This process creates a potential vulnerability. FHE solves this problem by enabling computations to occur directly on encrypted data. The result of these computations is also encrypted. Only the intended recipient can decrypt and view the final output. This eliminates the need for intermediate decryption steps which can help significantly reduce the risk of data breaches.

This challenge is critical in the Web3 space. Traditional methods expose projects to potential breaches during data processing. This might undermine user trust and system integrity. Fully Homomorphic Encryption (FHE) addresses these challenges by an innovative approach that not only enhances security but also eliminates the risks associated with intermediate data handling.

FHE encryption has become a critical tool for Web3 projects. It allows them to securely process user and transactional data without compromising privacy. This aligns perfectly with the principles of decentralization and transparency that underpin the Web3 ecosystem.

3 Key Terminologies of FHE

FHE relies on three key terminologies to ensure the secure data processing. Each key plays a specific role in enabling computations on encrypted data.

1. Decryption Key

The decryption key is the "master key" in the cryptosystem. It is the only key that can unlock encrypted data after processing. Only authorized users with access to the decryption key can view the original or processed data. By safeguarding this key, FHE encryption guarantees that sensitive information remains secure and private throughout the data lifecycle.

2. Encryption Key

The encryption key is used to lock the data before it is shared or stored. This key ensures that the data will not be accessible to unauthorized parties. This key is shared with other parties to allow them to encrypt data that can only be decrypted with the corresponding decryption key. The encryption key is fundamental to preserving data confidentiality at the initial stage.

3. Evaluation Key

The evaluation key is a  publicly available key that enables computations on encrypted data without revealing its contents. It allows authorized parties to process encrypted data while ensuring that the data remains protected. 

Methods on Fully Homomorphic Encryption

1. Outsourcing Mode

Outsourcing Mode is one of the first methods being used for Fully Homomorphic Encryption. It allows encrypted data to be sent to a third-party server for data processing on behalf of the first party. This method is particularly useful when local computational resources are limited.

How Outsourcing Mode Works

1. Encrypt Data
   The data owner encrypts their data using an encryption key.

2. Send to Server
   The encrypted data is sent to a third-party processor, who acts as the receptor party.

3. Process Encrypted Data
   The receptor performs computations on the encrypted data without needing to decrypt it.

4. Return Encrypted Result
   The receptor sends back the processed encrypted data to the data owner.

5. Decrypt Result
   The data owner uses the decryption key to unlock the final result.

In this process, the receptor has no access to the original data. This helps ensure privacy even if the server is compromised.

Pros of Outsourcing Mode

1. Data Privacy
   The data remains encrypted during the process. There will be no external servers that can access the data which maintain the risk of vulnerability.

2. Efficiency
   Resource-intensive computations can be offloaded by leveraging external servers.

3. Cost Savings
   Organizations can avoid the expense of building and maintaining in-house infrastructure for complex computations.

4. Scalability
   Cloud services provide the flexibility to scale operations for large or complex datasets.

Cons of Outsourcing Mode

1. Reliance on Providers
   Trusting third-party servers to handle encrypted data securely is necessary, which may raise concerns.

2. Performance Overhead
   FHE computations lead to slower processing compared to non-encrypted methods.

3. Data Transfer Time
   Transferring large encrypted datasets to external servers can be time-consuming.

4. Complexity
   Managing encryption keys, secure data transfer, and computational workflows adds operational complexity.

2. Two-Party Computation

Two-Party Computation or 2PC is a joint operation where two parties collaboratively compute a function on their combined data without revealing their individual inputs. 

Use Case Example: The Millionaire Problem

A classic example of 2PC is the "Millionaire Problem". There are two individuals (A and B) want to compare their wealth without disclosing their exact net worth.

• A encrypts her net worth and sends the encrypted data to the computation server.

• B does the same, sending his encrypted data.

• The server processes the combined encrypted data using FHE encryption and determines the wealthier individual.

• The result is shared with both A and B, showing only who is wealthier without revealing their specific net worth.

Pros and cons of Two-Party Computation

How FHE Ensures Secure and Legitimate Processing

Fully Homomorphic Encryption incorporates mechanisms that protect encrypted data from tampering while ensuring that only the intended final results are accessible. Here are the mechanisms it uses:

1. Evaluation Key Control
   Only approved computations can be performed on the encrypted data, ensuring that unauthorized or malicious functions cannot compromise the process.

2. Data Integrity Safeguards
   This makes tampered data unusable when decrypted. Any unauthorized modifications during computation will not yield valid results.

How FHE Protects the Final Results

FHE encryption ensures that only the final computation result is decrypted. Intermediate values and steps remain encrypted and inaccessible, reducing exposure risks. This guarantees that sensitive data is not revealed during the computation process.

The decryption key required to access the final result is held solely by the intended recipient. This ensures that no unauthorized party, including those performing the computations, can access the final decrypted data.

Building Blocks of Fully Homomorphic Encryption

Homomorphic encryption depends on essential cryptographic elements or building blocks. Each of these building blocks maintains data privacy and integrity during computations. 

1. Public-Key Encryption
   Data is encrypted with a public key and can only be decrypted by the private key holder.

2. Ciphertext Manipulation
   Allows operations (e.g., addition, multiplication) on encrypted data without decryption.

3. Evaluation Key
   Enables authorized computations on encrypted data by third parties without decryption.

4. Secure Multi-Party Computation
   Allows multiple parties to compute jointly on encrypted data without exposing their private inputs.