Exploring the Connotation and Application Prospects of Fully Homomorphic Encryption Technology

Recently, the market trend has slowed down, providing us with more time to focus on the development of emerging technologies. Although the cryptocurrency market in 2024 may not be as spectacular as in previous years, there are still some new technologies gradually maturing. Today, we will focus on a remarkable technology—fully homomorphic encryption (FHE).

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

Basic Concepts of encryption

Encryption is a common method for protecting information security. For example, if Alice wants to send a confidential message "1314 520" to Bob through a third party, she can use a simple encryption method, such as multiplying each number by 2, turning it into "2628 1040". When Bob receives it, he only needs to divide each number by 2 to decrypt the original message. This method allows Alice and Bob to securely exchange information without trusting the intermediary.

The Principle of Homomorphic Encryption

Homomorphic encryption goes a step further, allowing computations to be performed on encrypted data without the need for decryption first. For example, Alice needs to calculate the total electricity bill for her home over 12 months (400 yuan per month), but she is not good at complex calculations and does not want to reveal the specific amount. She can encrypt 400 and 12 by multiplying each by 2, and then ask someone to compute the result of 800×24. After obtaining 19200, Alice can simply divide the result by 4 to find out that the actual total electricity bill is 4800 yuan. In this process, the calculator cannot know the original data, which reflects the characteristics of homomorphic encryption.

The Necessity of Fully Homomorphic Encryption

However, simple Homomorphic Encryption may be cracked. To increase security, more complex encryption methods need to be introduced, such as multiple multiplication and addition operations. Fully homomorphic encryption allows for any number of addition and multiplication operations to be performed on encrypted data, greatly enhancing security and making it nearly impossible for third parties to infer the original data.

The Application Prospects of FHE Technology

FHE technology has broad application prospects in the field of artificial intelligence. AI models require a large amount of data for training, but this data often involves privacy. FHE allows for the processing of encrypted data by AI while protecting data privacy. For example, users can encrypt sensitive data and provide it to AI for computation, and AI returns the encrypted result, which the user can decrypt locally to obtain the required information, ensuring that AI cannot access the original data throughout the entire process.

This technology is of great significance for scenarios that require privacy protection, such as facial recognition. It can achieve functions like identity verification without disclosing personal sensitive information.

Challenges and Solutions of FHE

Despite the broad prospects of fully homomorphic encryption (FHE), its practical applications face enormous computational resource demands. To address this issue, some projects are developing specialized hardware and network architectures. For example, certain projects propose network structures that combine Proof of Work (PoW) and Proof of Stake (PoS) mechanisms, and have developed dedicated mining equipment to establish a powerful computing network to support FHE computations.

The Impact of FHE on AI and Data Privacy

If FHE technology can be widely applied in the field of AI, it will greatly alleviate the current data privacy and security issues faced by AI development. From personal privacy protection to national security, FHE may play an important role. In the future AI era, FHE technology is likely to become the last line of defense in protecting human privacy.

With the continuous advancement of technology, we look forward to seeing the application of FHE in more fields, bringing new possibilities for data security and privacy protection.