Demystifying FHE Technology: Exploring Data Privacy Solutions Beyond Zero-Knowledge Technology

Since the advent of Bitcoin in 2009, blockchain technology has evolved dramatically, transforming from a simple cryptocurrency ledger to a platform widely used in decentralized applications. Its fundamental properties—immutability, transparency, and decentralization—have established blockchain as a solid framework for secure data transactions, eliminating the need for traditional intermediaries.

Despite the advancements in blockchain technology, concerns about data privacy remain. While blockchain ensures the security of data transmission through encryption, the decryption process in order to process the data can present potential security holes. This vulnerability is particularly significant in areas where data confidentiality and integrity are critical, such as decentralized applications (dApps) and financial systems running within the Web3 framework.

To mitigate these risks, advanced encryption methods such as fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKP) have become increasingly important. These technologies provide a revolutionary way to compute and verify the confidentiality of data without revealing the underlying sensitive information.

In this article, we will provide an in-depth analysis of the key role of FHE and ZKP in improving the privacy of blockchain applications, and emphasize the importance of the development potential of these technologies in the field of future blockchain data privacy.

Introduction

The history of FHE and ZKP goes back decades. Both have undergone significant evolution over time and still play an important role in enhancing data privacy.

Fully Homomorphic Encryption (FHE)

FHE is a sophisticated encryption method that allows functions to be performed directly on encrypted data, thus maintaining its confidentiality throughout the process. Essentially, FHE keeps data encrypted during storage and computation, treating encryption as a secure "black box" where only the owner of the key can decrypt the output. The concept of FHE was first proposed in 1978 to modify computer hardware to enable secure processing of encrypted data. However, it was not until 2009 that a viable FHE solution became available due to advances in computing power. This breakthrough is largely due to Craig Gentry, whose innovative work marked a major milestone in the field.

<img src="/static/imghwm/default1.png" data-src="https://img.php.cn/upload/article/000/887/227/171506727041753.png?x-oss-process=image/resize,p_40" class="lazy" alt="Demystifying FHE Technology: Exploring Data Privacy Solutions Beyond Zero-Knowledge Technology">图片来源于 Zama

Explanation of key terms:

• Fully homomorphism (Fully): Indicates the ability to perform various operations on encrypted data, such as addition and multiplication.
• Homomorphic: refers to the ability to directly perform calculations on encrypted data without decrypting it.
• Encryption: Describes the process of converting information into a secure format to prevent unauthorized access.

The field of FHE has made significant progress since 2009, with a major breakthrough occurring in 2013 that simplified the relinearization process and significantly improved the efficiency of FHE. These developments demonstrate FHE's ability to perform a variety of arithmetic operations on encrypted data, protecting the security and integrity of the data without exposing the data content.

Zero-knowledge proof (ZKP)

ZKP was first proposed in 1985 in the seminal paper "Knowledge Complexity of Interactive Proof Systems" by Shafi Goldwasser, Silvio Micali, and Charles Rackoff. ZKP was originally a theoretical concept, and it was not until the emergence of zk-SNARKs in 2012 that it saw significant development. zk-SNARKs are a type of ZKP that can verify the authenticity of any computation without revealing almost any information.

In a typical ZKP, there are two main roles: prover and verifier. The prover's goal is to confirm a specific statement, and the verifier's role is to evaluate the truth of the statement without learning any additional information. This approach allows the prover to disclose only the necessary evidence needed to verify the statement, thus protecting the confidentiality of the data and enhancing privacy.

With the rise of blockchain technology and cryptocurrency, the practical applications of ZKP have increased dramatically. They are crucial in facilitating private transactions and enhancing smart contract security. The emergence of zk-SNARKs has led to the development of solutions such as zCash, zkRollups, and zkEVMs, transforming what was once an academic pursuit into an ecosystem full of real-world applications. This shift highlights ZKP’s growing relevance in securing decentralized systems like Ethereum and driving strong privacy-focused digital infrastructure.

ZK vs FHE

Although there are some similarities between FHE and ZKP, there are significant functional differences. FHE can perform computations directly on encrypted data without leaking or accessing the original data, producing accurate results without exposing the underlying information.

图片来源于 Morten Dahl的研讨会

The two technologies differ in the following ways:

Encrypted Computing

ZKP handles encrypted data from multiple users (such as private ERC-20 tokens) without compromising security. In contrast, FHE excels in this regard, providing greater flexibility and composability to blockchain networks. However, ZKP often requires custom integration for each new network or asset.

Scalability

Currently, ZKP is widely considered to be more scalable than FHE. However, as technology continues to advance, the scalability of FHE is expected to improve in the coming years.

Complex Computation

FHE is well suited for complex computations on encrypted data, making it ideal for applications such as machine learning, secure MPC, and fully private computation. In contrast, ZKP is typically used for simpler operations, like proving a specific value without leaking it.

Universal Applicability

ZKP excels in specific applications such as authentication, authentication and scalability. However, FHE can be used in a wider range of application areas, including secure cloud computing, privacy-preserving artificial intelligence and confidential data processing.

This comparison highlights the unique strengths and limitations of each technology, illustrating their relevance to different scenarios. Both technologies are important components of blockchain applications, but ZKP currently has a more mature application record. Nonetheless, FHE is expected to evolve in the future and may become a more suitable solution for privacy protection in the future.

Joint applications of ZKP and FHE

Some applications have tried interesting ways of combining ZKP and FHE. Notably, Craig Gentry and colleagues have explored using hybrid fully homomorphic encryption techniques to reduce communication overhead. These innovative technologies have been applied in various blockchain scenarios and have potential to be explored in other areas.

Potential applications of the combination of ZKP and FHE include:

1. Secure cloud computing: FHE encrypts data, while ZKP verifies its correctness, making it secure in the cloud Computations become possible without exposing raw data.

2. Electronic voting: Its combination ensures the confidentiality of the ballot and confirms an accurate count.

3. Financial Transactions: In the financial sector, this integration maintains the confidentiality of transactions while allowing parties to verify their correctness without revealing details.

4. Medical Diagnosis: Medical data is encrypted so it can be analyzed by medical providers, who can confirm diagnoses without accessing sensitive patient information.

The joint application of ZKP and FHE promises to enhance identity and data security in applications and is well worth further exploration and research.

Current FHE Projects

The following are some projects dedicated to applying FHE technology in the blockchain field:

• Zama: A company dedicated to Open source cryptography company developing FHE solutions for blockchain and artificial intelligence.

• Secret Network: A blockchain platform launched in 2020 that integrates privacy-preserving smart contract functions.

• Sunscreen: A compiler designed for FHE and ZKP.

• Fhenix: A confidential Layer 2 blockchain leveraging FHE technology.

• Mind Network: A universal restaking rollup solution based on FHE.

• Privasea: A data infrastructure platform using FHE technology to facilitate computing on encrypted data.

Summary

FHE is quickly establishing itself as an integral part of cybersecurity, especially in the cloud computing space. Industry giants such as Google and Microsoft are adopting the technology to securely process and store customer data without compromising privacy.

This technology promises to redefine data security across platforms, heralding an era of unprecedented privacy. Achieving this future requires continued advancement of technologies such as FHE and ZKP. Collaboration across disciplines, including cryptographers, software engineers, hardware experts, and policymakers, is critical to navigate the regulatory environment and promote broader adoption.

As we move towards a new era of digital sovereignty, it is crucial to stay up to date on the latest developments in areas such as FHE and ZKP, where data privacy and security are seamlessly integrated. Keeping information updated will enable us to effectively navigate this evolving landscape and realize the full potential of these advanced encryption tools.

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