Fully Homomorphic Encryption (FHE): A Privacy Protection Tool in the AI Era

Recently, the market has been sluggish, giving us more time to focus on some emerging technologies. Although the cryptocurrency market in 2024 is not as dramatic as in previous years, there are still some new technologies that are gradually maturing, one of which is the topic we will discuss today: fully homomorphic encryption (FHE).

To understand the complex concept of FHE, we first need to understand what "encryption", "homomorphic" is, and why it should be "fully".

1. Basic Concepts of encryption

Encryption is a method of protecting information security. To give a simple example, if Alice wants to send the message "1314 520" to Bob through a third party C, and she does not want C to know the content, she can use a simple encryption method: multiplying each number by 2. In this way, the transmitted information becomes "2628 1040". When Bob receives it, he only needs to divide each number by 2 to decrypt the original message. This method is a basic form of symmetric encryption.

2. The Concept of Homomorphic Encryption

Homomorphic Encryption goes a step further by allowing computations on encrypted data without needing to decrypt it first. Suppose Alice is only 7 years old and can only perform the simplest operations of multiplying by 2 and dividing by 2. Now she needs to calculate the total electricity bill for her home for 12 months, which is 400 yuan each month, but she cannot perform such a complex calculation.

She can do it this way: multiply both 400 and 12 by 2 to get 800 and 24, then have C calculate 800 multiplied by 24. After C calculates the result of 19200, he tells Alice, who then divides this result by 2 and then by 2 again, resulting in the correct answer of 4800 yuan. During this process, C does not know what Alice is actually calculating, which is a simple example of homomorphic encryption for multiplication.

3. The Necessity of Fully Homomorphic Encryption

However, simple homomorphic encryption can be compromised. For example, C may infer through exhaustive search that Alice was originally going to compute 400 and 12. This requires a more complex encryption method, which is fully homomorphic encryption.

Fully homomorphic encryption allows for arbitrary addition and multiplication operations on encrypted data and ensures that the correct results are obtained after decryption. This technology can handle more complex mathematical problems while virtually eliminating the possibility of third-party eavesdropping on private data.

It was not until 2009 that Gentry and other scholars proposed new ideas, which truly opened the door to fully homomorphic encryption.

The Application of FHE in the AI Field

FHE technology has huge potential in the AI field. AI requires a large amount of data for training, but much of the data is highly private. FHE can solve this contradiction:

1. Use FHE to encrypt sensitive data
2. Train AI with encrypted data
3. AI outputs encryption results
4. The data owner securely decrypts the results locally.

This not only protects data privacy but also fully utilizes the powerful computing capabilities of AI.

Real-World Applications of FHE

FHE technology can be applied in many fields, such as facial recognition:

• Requirement: Determine if it is a real person
• Challenge: Cannot disclose sensitive facial information FHE can effectively solve this problem.

However, FHE computation requires enormous computing power. To this end, some projects are building dedicated computing networks and supporting facilities.

The Importance of FHE for AI Development

If AI can widely apply fully homomorphic encryption (FHE) technology, it will greatly alleviate the current data security and privacy issues. From national security to personal privacy protection, FHE has broad application prospects.

In this rapidly developing era of AI, the maturity of FHE technology may become the last line of defense in protecting human privacy. Whether it is protecting military intelligence in international conflicts or safeguarding personal privacy in daily life, FHE will play an important role.

As time goes by, the influence of AI will only grow stronger. In this context, the importance of FHE technology is self-evident. It is not only a technological innovation but also a key tool for safeguarding individual rights in the digital age.