Exploring Privacy Solutions in Blockchains: ZKPs, FHE, MPC.

Table of Contents

The evolution of blockchain technology has not only transformed financial transactions but has also ushered in an era of increased transparency. However, this transparency has come at the cost of compromising user privacy. In this article, we dive into the world of cutting-edge privacy technologies – Zero-Knowledge Proofs (ZKPs), Fully Homomorphic Encryption (FHE), and Multi-Party Computation (MPC) – exploring their applications, challenges, and the promising synergy they offer for on-chain privacy.

I. Privacy Technologies Overview:

In the ever-evolving landscape of blockchain and decentralized technologies, privacy stands out as a crucial pillar that demands attention. Let's delve deeper into the fundamental technologies driving on-chain privacy and their distinctive characteristics.

A. Zero-Knowledge Proofs (ZKPs):

source: CO6GC

Zero-Knowledge Proofs (ZKPs) have emerged as a cornerstone in the quest for privacy on the blockchain. Originating with projects like zCash in 2016, ZKPs enable users to interact with the blockchain without revealing the underlying data. This cryptographic technique empowers individuals to prove the authenticity of their actions without disclosing sensitive information.

Applications and Challenges:

ZKPs have found their stride in applications such as payment networks. Notable examples include zCash and Iron Fish, where users can transact privately, locally computing changes to their private data and generating proofs for the network. Despite their utility, challenges persist, particularly in terms of user-side computation and limitations in dealing with shared private states.

B. Fully Homomorphic Encryption (FHE):

source: chainlinkblog

Fully Homomorphic Encryption (FHE) introduces a paradigm shift by allowing computations over encrypted data, a breakthrough that opens new doors for privacy in on-chain applications. FHE excels in scenarios where multiple parties need to perform computations on shared private states while keeping the underlying data encrypted.

Advantages, Limitations, and Applications:

The advantages of FHE are manifold, with enhanced composability being a standout feature. Multiple transactions or users can concurrently modify the same private state, offering unprecedented flexibility. However, the computational complexity of FHE poses challenges, limiting the throughput of on-chain applications to 1-5 transactions per second. Despite this, FHE finds applications in information-incomplete games, private voting, and private Automated Market Makers (AMMs).

C. Multi-Party Computation (MPC):

source: Qredo blog

Multi-Party Computation (MPC), initially renowned for its role in secure asset custody, has evolved into a versatile tool for computing over private data in blockchains. In essence, MPC enables collaborative computation without exposing the individual inputs, providing a unique blend of privacy and functionality.

Use Cases and Limitations:

MPC finds applications in Dark Pool Central Limit Order Books (CLOBs), decentralized AI training, and more. Its strengths lie in ensuring strong privacy guarantees, but limitations arise concerning the necessity for cooperation among MPC parties and potential risks associated with censorship.

Understanding these privacy technologies lays the groundwork for exploring their diverse applications, synergies, and challenges in the blockchain space. As we journey deeper into the realm of on-chain privacy, these technologies collectively shape a more secure and confidential future for decentralized systems.

II. Applications of Privacy Technologies

Privacy technologies are unlocking a myriad of applications, reshaping the dynamics of on-chain interactions and expanding the possibilities within the blockchain ecosystem.

Anonymous Social Media and Private Credentials

Picture a novel social media paradigm where participants can openly express themselves without fear of social repercussions. Privacy technologies facilitate the creation of anonymous social media platforms where users can securely share certain traits about themselves on-chain, such as their on-chain wealth or ownership of specific NFTs. This innovative approach enables individuals, including high-profile figures, to post anonymously, leveraging on-chain proof of traits like never before. Projects like Whale Songs, including prototypes like those developed by colleagues such as David, are pioneering this new frontier.

Additionally, the concept of private credentials comes into play. Users with specific credentials, such as qualifications or expertise, can participate in decentralized autonomous organizations (DAOs) or contribute to on-chain protocols anonymously. Platforms like HeyAnoun exemplify this approach, extending the application domain to include leveraging real-world credentials like financial status or academic degrees. Onboarding private, real-world credentials onto the blockchain opens avenues for uncollateralized DeFi lending, on-chain KYC, and geographical gating.

Enterprise Invoicing and Payments

In the realm of enterprise transactions, Fully Homomorphic Encryption (FHE) takes center stage. Companies often prefer to keep their business partners, suppliers, and contractual terms confidential. On-chain transparency has historically hindered the adoption of stablecoin payments in the enterprise sector. However, with the integration of on-chain privacy technologies, enterprises can enjoy the benefits of on-chain payments, unlocking improved efficiency and cost-effectiveness compared to traditional banking rails.

The enhanced privacy offered by FHE allows enterprises to conduct on-chain invoicing and payments securely, addressing concerns related to revealing sensitive business information. As a result, the adoption of on-chain payments within the enterprise sector is expected to accelerate, further bridging the gap between traditional financial systems and blockchain technology.

Information-incomplete Games, Private Voting, and Private AMM

Privacy technologies play a pivotal role in crafting new paradigms for games, voting systems, and decentralized finance (DeFi) applications:

- Information-incomplete Games: Privacy technologies enable the creation of information-incomplete games, transforming the landscape of gaming on the blockchain. Examples include card games like poker, where the status of the card deck is accessible and can be modified by multiple players, introducing a new layer of strategy and privacy to gaming experiences.

- Private Voting: Secure and private voting systems become a reality through the application of privacy technologies. Fully Homomorphic Encryption (FHE) simplifies the implementation of secret polls, allowing votes to change the voting tally without disclosing previous results. This paves the way for secure and confidential voting mechanisms within blockchain-based systems.

- Private AMM (Automated Market Makers): Decentralized finance (DeFi) applications benefit significantly from on-chain privacy technologies. FHE, in particular, simplifies the implementation of private AMM pools, offering a secure environment for users to conduct transactions without revealing sensitive details. Dark Pool CLOBs (Central Limit Order Books) exemplify the fusion of Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs) to create secure and private AMM systems.

III. Synergies and Challenges Among ZKPs, FHE, and MPC

The interplay between Zero-Knowledge Proofs (ZKPs), Fully Homomorphic Encryption (FHE), and Multi-Party Computation (MPC) reveals a nuanced relationship, highlighting both synergies and challenges within the realm of on-chain privacy.

A. Addressing Privacy Trust Assumptions and Composability Challenges

-Privacy Trust Assumptions

Zero-Knowledge Proofs stand out for their robust privacy guarantees, ensuring that unencrypted data never leaves the user's device. This inherent security is further strengthened by the impossibility of running computations over the data without the owner's explicit permission. However, this level of privacy comes at the cost of weakened composability. The challenge lies in striking a balance between robust privacy and the seamless composability essential for the growth of blockchain ecosystems.

-Composability Challenges

On the other hand, Fully Homomorphic Encryption enhances composability but introduces trust assumptions. The reliance on a small number of entities with global FHE decryption keys raises concerns about potential privacy leakage. Despite these challenges, FHE's ability to enable privacy in critical use cases like decentralized finance (DeFi) showcases its potential to revolutionize on-chain interactions.

Multi-Party Computation offers a middle ground, allowing computing over shared private data. While it enhances composability, the limitation lies in its permissioned nature. Only entities within the MPC group can perform computations, introducing a controlled environment for privacy and computations.

B. Striking the Right Balance

The discussed approaches—ZKPs, FHE, and MPC—may appear competitive at first glance, but they are, in fact, complementary technologies. Zero-Knowledge Proofs offer unparalleled privacy, ensuring data remains within the user's control. FHE enhances composability, enabling multiple transactions/users to change the same private state within a block. MPC introduces a unique middle ground, allowing secure computations over private data but within a restricted, permissioned setting.

-Examples of Combined Approaches

In practice, the combination of these technologies is increasingly common. Renegade Finance's use of both MPC and ZKPs in its Dark Pool CLOB exemplifies the potential of blending these technologies to create innovative, privacy-focused applications. Similarly, on-chain poker games, like zkHoldem, combine Zero-Knowledge Proofs and Fully Homomorphic Encryption to deliver a secure and private gaming experience.

As the blockchain ecosystem matures, the collaboration between ZKPs, FHE, and MPC is anticipated to become a standard practice. The integration of these technologies ensures that developers have a diverse toolkit to address the unique challenges posed by various on-chain applications, fostering a more secure, private, and interconnected blockchain landscape.

IV. Future Trends

As we gaze into the future of on-chain privacy, a multitude of trends and developments are poised to shape the landscape, offering exciting possibilities and addressing the evolving needs of the blockchain ecosystem.

Anticipated Developments in On-chain Privacy

The rapid pace of innovation within privacy technologies suggests several key developments on the horizon:

1. Usability Improvements: A major focus is expected on enhancing the usability of on-chain privacy technologies. Simplifying user-side computations and streamlining processes will contribute to a more seamless and user-friendly experience. This, in turn, will broaden the adoption of privacy-focused applications.

2. Developer Experiences: The integration of Zero-Knowledge Proofs (ZKPs), Fully Homomorphic Encryption (FHE), and Multi-Party Computation (MPC) is likely to become more developer-friendly. Efforts to lower the barriers for developers, allowing them to efficiently navigate the intricacies of on-chain private applications, will play a crucial role in driving innovation.

3. General Programmability: The trend towards general programmability within privacy technologies is set to continue. Networks such as Aztec and Aleo, with their high-level programming languages like Noir and Leo, are leading the way in abstracting complexity for application developers. General programmability enables the creation of diverse applications, expanding the use cases for on-chain privacy.

Alliance's Commitment to Supporting Privacy-Focused Innovations

In this era of transformative developments, Alliance stands as a beacon for those spearheading innovations in on-chain privacy. The commitment to supporting founders building the future is a cornerstone of Alliance's vision. By fostering collaboration and providing resources to pioneers in the privacy infrastructure space, Alliance aims to propel the growth of privacy-centric networks and applications.

Conclusion

The trio of Zero-Knowledge Proofs (ZKPs), Fully Homomorphic Encryption (FHE), and Multi-Party Computation (MPC) emerges as a powerful solution, offering a diverse toolkit for developers.

Applications span social media, enterprise transactions, gaming, and voting, showcasing the versatility of on-chain privacy. Collaborative efforts by pioneers like Renegade Finance and others illustrate the potential of blending these technologies for secure, private, and interconnected applications.

Future trends emphasize user-centric improvements and developer-friendly experiences. Alliance's commitment to supporting privacy-focused innovations calls founders in the space to shape a future where on-chain privacy is integral to Web 3.0.

As we conclude, this exploration is not an endpoint but a prologue to a privacy-centric era. Alliance invites visionaries to join the journey, crafting a transformative future where privacy and innovation seamlessly intertwine in decentralized ecosystems.

About Orochi Network

Orochi Network is a cutting-edge zkOS (An operating system based on zero-knowledge proof) designed to tackle the challenges of computation limitation, data correctness, and data availability in the Web3 industry. With the well-rounded solutions for Web3 Applications, Orochi Network omits the current performance-related barriers and makes ways for more comprehensive dApps hence, becoming the backbone of Web3's infrastructure landscape.