While in Web2 space data encryption is a well-established and required standard, it seems that the ‘lack-of-encryption’ for commercially sensitive and personal data in Web3 is still a growing and evolving threat. To scale the industry forward, privacy must be an integral part of blockchain, meaning that data encryption and computation capabilities should be key features of all blockchains.

To address this challenge we need to bring developers the infrastructure and tools that allow easy integration of robust data encryption capabilities in the applications that are essential for this space to grow.

Fhenix is rising to this challenge.

Fhenix is building the first confidential smart contract platform using fully homomorphic encryption (FHE). FHE is a novel cryptographic scheme that enables direct computation over encrypted data without ever revealing the underlying data. Fhenix’s goal is to advance application development in the blockchain ecosystem by bringing data encryption and encrypted data computation to smart contracts, transactions, and on-chain assets for the first time.

By leveraging the power of FHE, Fhenix redefines how sensitive data is being managed in the blockchain ecosystem, envisioning a future where privacy and decentralization are not at odds, but rather, complementary aspects of a secure digital economy.

Fully Homomorphic Encryption

FHE is considered the holy grail of cryptography, as it enables direct computation over encrypted data while never revealing the data to the server, or in the context of blockchains — to validators or sequencers. This is all groundbreaking, with recent breakthroughs paving the way for Homomorphic Encryption data processing to arrive at last on the blockchain.

This means that Fhenix now enables a wide array of versatile use cases such as:

• • Trustless Gaming: Every game that requires players to hide their information from other players, like on-chain casino gaming, where you need to hide information between opponents or the dealer, while still allowing computation on the data.
  • Private Voting: Both on-chain and off-chain voting mechanisms can operate with fully encrypted variables, ensuring confidentiality without sacrificing trustworthiness.
  • Privacy-Preserving AI: The ability to compute encrypted data opens the door for on-chain artificial intelligence applications, thereby expanding the range of possible use cases exponentially.
  • Confidential Token Transfers: P2P payments, commercial transactions, and other sensitive transfers can be made private, yet auditable.

These are all multi-billion dollar industries growing at a rapid pace, but applicability also extends to areas such as blind auctions, MEV protection, account abstraction, and confidential DAOs. We are also merely at the beginning of what’s truly possible, with many use cases undiscovered.

This is all possible due to fhEVM, which we’ll cover next.

The Gold Standard: fhEVM

fhEVM is a set of extensions for the Ethereum Virtual Machine (EVM) that allows Solidity developers to seamlessly create encrypted smart contracts without any cryptographic expertise. Solidity is the most popular Web3 language to date and comes with an extensive suite of developer tools and libraries, making fhEVM extremely easy to begin working with.

This is important, as blockchains that rely upon entirely novel programming languages have significant costs associated with attracting and training developers to begin using their unique language. In contrast, fhEVM taps into the expansive EVM community and enables developers to easily begin deploying new, innovative projects.

Fhenix also has a modular, extension-like design which means that its ability to compute encrypted data can be integrated across all blockchain layers, enabling the easy development of confidential smart contracts on public blockchains. For example, developers can now build applications around encrypted data, such as decentralized email services or private voting.

This comes in the form of the Fhenix SDK which can now be used by developers to add encryption capabilities to their existing products, seamlessly, without any changes to their existing smart contracts.

Fhenix’s limited access devnet was deployed in July 2023, and provides an approachable FHE playground where the fhEVM is already functional and in use. To apply for early access click here.

The Confidential Compute Constellation: Blockchain’s Encryption-First Future

While public blockchains are pseudonymous in nature, this is insufficient for many blockchain applications and will become increasingly easy to correlate on-chain activity with real-world identities. Also, It is important to understand that confidentiality is not a “one-size-fits-all” issue solved by one technology alone. Like in blockchains, there are multiple tradeoffs between confidentiality technologies, such as security, scalability, decentralization, complexity and cost.

This insight led to the formation of the Confidential Compute Constellation: a collective of interconnected confidential solutions serving as an encryption hub for Web 3.0.

The Confidential Computing Constellation starts by combining Secret Network’s battle-tested platform, experience and community with the novel Fully Homomorphic Encryption technology that Fhenix introduced into a full-fledged smart contract platform.

The goal of the Constellation is to combine a wide range of confidential-computing technologies and solutions to create a single hub for privacy and confidentiality on Web3, offering confidential computing applications on member networks and providing privacy as a service to the EVM ecosystem and beyond.

What is FHE?

In 1978, researchers first examined the issues surrounding modifying computer hardware in order to perform secure operations on encrypted data. For the following 30 years little progress was made, primarily due to insufficient computing power required for such complex computations.

In 2009, progress resumed when a possible FHE scheme was proposed by Craig Gentry. This coincided with significant increases in computing power that fueled early progress in artificial intelligence. Further progress has since been made, including a groundbreaking research paper in 2013 that sidestepped FHE’s computationally expensive relinearization step, have helped lead us to the present day.

At long last, the “once mythical” technology known as Fully Homomorphic Encryption has arrived, allowing us to conduct confidential computing. At its core, confidential computing introduces a totally new paradigm of securing data, and performing secure computations.

So what does Fully Homomorphic Encryption actually mean? Let’s consider each term separately:

1. Fully: In the context of FHE, fully means that arbitrary operations such as addition and multiplication are supported.
2. Homomorphic: The ability to allow computations on encrypted data without first decrypting it.
3. Encryption: The process of converting information into code that prevents unauthorized access.

Taken together, FHE refers to the ability to perform binary operations on encrypted data without decrypting the data — ever. Kind of like magic.

Binary operations refer to mathematical operations that take two inputs and produce a single output — such as addition, multiplication, subtraction, and division. Blockchains, at their core, primarily deal with integer operations, meaning that this is tremendously valuable for the industry as a whole.

FHE’s Significance to Blockchain

The status quo requires data to first be decrypted in order to run computations on it. It must then be encrypted again, and later decrypted, with each step presenting new opportunities for the data to be exploited.

This has contributed to major data exploits in nearly every industry, impacting hundreds of millions and the biggest firms including Equifax, Marriot International, EasyJet, and countless more. Each exploit of sensitive data costs billions to rectify, and exposes the personal data of millions. FHE’s ability to compute encrypted data has far reaching ramifications for nearly every industry and will become the new standard for data security.

How can this be implemented?

While future content will cover FHE at a technical level, here we will provide a simple overview in regards to how FHE would integrate in blockchain. Keep in mind that FHE has far reaching implications beyond just the blockchain industry — but this space is our focus.

As mentioned, blockchains primarily deal with integer operations, such as managing smart contract “states”, updating block indices, or processing cryptocurrency transactions. This means that applying FHE onto encrypted blockchain data is extremely powerful.

That being said, FHE is niche and very complex, so the barrier to entry is high. That’s why we’ve partnered with Zama, which built the fhEVM.

fhEVM is a set of extensions for the Ethereum Virtual Machine (EVM) that allows any Solidity developers to integrate FHE into their workflow. This enables the creation of encrypted smart contracts without any FHE expertise and means that developers can benefit from Solidity’s extensive suite of developer tooling.

fhEVM is used for writing the application itself, but we also have fhenix.js which allows developers to create the frontend using Javascript.

FHE vs. ZK

Zero-knowledge (ZK) technology has been widely covered in recent times, often heralded as the future of blockchain privacy.

It’s important to note some distinctions from FHE:

• Encryption computation: ZK cannot compute over encrypted data from multiple users (which would be the case for private ERC-20 tokens) without sacrificing security. FHE can do so, which makes it more composable throughout blockchain. ZK technology often requires custom integrations for new networks and assets.
• Scalability: ZK is considered more scaleable than FHE, at least at the present moment. Technological developments will scale FHE over the coming years.
• Complex calculations: FHE can handle complex calculations on encrypted data, suitable for needs such as machine learning, secure MPC, and fully private computations. In contrast, ZK Proofs are typically users for simpler tasks such as proving a value without revealing it.
• Universal Applicability: while ZK Proofs are great for specific use-cases like identity verification, authentification, and scalability, FHE can be applied to a broader range of applications. This includes confidential data processing, secure cloud computing, and privacy-preserving AI applications.

We believe that both have their place in blockchain. However, while ZK technology is more mature than FHE at the present moment, we believe that FHE will ultimately emerge as the most suitable privacy-preserving solution.

For more information, we covered the fhEVM in greater depth in our last blog post.