Exploring Fully Homomorphic Encryption Technology: A Privacy Protection Tool in the AI Era

Recently, although the cryptocurrency market has not experienced much volatility, there are still some emerging technologies gradually maturing. Among them, fully homomorphic encryption (FHE) technology is a direction worth paying attention to. In May of this year, Ethereum founder Vitalik Buterin also published an article specifically about FHE, which sparked widespread discussion within the industry.

To understand the complex concept of FHE, we need to first understand the meanings of "encryption" and "homomorphic", and why we need to achieve "fully" homomorphic encryption.

encryption的基本概念

Encryption is a common method used to protect information security. For example, Alice wants to send a secret message "1314 520" to Bob through a third party, C. To keep it confidential, Alice can multiply each number by 2 for simple encryption, turning it into "2628 1040". When Bob receives it, he just needs to divide each number by 2 to restore the original information. This is a basic symmetric encryption method.

The Principle of Homomorphic Encryption

Homomorphic Encryption goes a step further, allowing calculations to be performed directly on encrypted data without the need for decryption. Suppose 7-year-old Alice only knows the simplest operations of multiplying by 2 and dividing by 2; she needs to calculate her family's total electricity bill for 12 months (400 yuan per month). Alice can encrypt 400 and 12 by multiplying by 2, and then ask third party C to compute the result of 800×24. After C arrives at 19200, Alice divides the result by 4 to get the correct total electricity bill of 4800 yuan. In this process, C does not know the actual bill amount and the number of months, which reflects the characteristics of Homomorphic Encryption.

The Necessity of Fully Homomorphic Encryption

However, simple Homomorphic Encryption may be cracked. For example, C could deduce the original data through exhaustive methods. Therefore, more complex fully homomorphic encryption technology is required. Fully homomorphic encryption allows for arbitrary additions and multiplications to be performed on encrypted data, greatly increasing the difficulty of cracking. This makes fully homomorphic encryption an important breakthrough in cryptography, which only began to be realized after Gentry and other scholars proposed new ideas in 2009.

The Application Prospects of FHE in the Field of AI

FHE technology has broad application prospects in the AI field. AI model training requires a large amount of data, but much of the data involves privacy issues. FHE can allow AI models to compute and learn from encrypted data while protecting data privacy. Specifically speaking:

1. Data owners can use FHE to encrypt sensitive data.
2. Provide the encrypted data to AI for computation
3. AI outputs encryption results
4. The data owner securely decrypts the results locally.

This approach not only protects the privacy of the original data but also fully utilizes the computational power of AI, achieving the goal of "both and also".

FHE Projects and Practical Applications

Several projects are currently exploring FHE technology, such as Zama, Privasea, and Mind Network. Taking a facial recognition application as an example, FHE can allow AI to determine whether someone is a real person without exposing the user's facial information.

However, FHE computation requires enormous computing power. To address this issue, some projects are building dedicated computing networks and supporting facilities. For example, a certain project has launched hardware products similar to mining equipment, as well as a "work certificate" issued in the form of NFTs to incentivize users to participate in network construction.

The Important Significance of FHE

With the popularization of AI technology, data privacy issues are becoming increasingly prominent. From personal privacy to national security, FHE technology has potential important applications. For example, in the military field, FHE can allow parties to utilize AI technology while protecting sensitive information. In daily life, from smartphone facial recognition to various privacy data processing, FHE may play an important role.

If FHE technology can truly mature, it will become the last line of defense for protecting human privacy in the AI era, having a profound impact on individuals, enterprises, and nations.