Homomorphic encryption for on-chain privacy: FHE use cases and projects
Post705 words
Explains partially and fully homomorphic encryption, why public chains expose users to theft, surveillance and MEV, and FHE uses: blind auctions, confidential voting, trustless bridges and FHE rollups. Expects FHE hardware to bring 1000x speedups.
Key claims
Optimistic FHE rollups are possible now, ZK FHE rollups within about 3 years
FHE hardware accelerators by 2025 could speed FHE up 1000x or more
FHE could go from 5 TPS to 1000+ TPS
Privacy matters & true on-chain privacy will be a big enabler for many use cases.
One game-changing technology that allows computation on fully encrypted data is Homomorphic Encryption (HE). 🔒
Pay attention, this might give rise to a new narrative! 🥷
So what is (full) HE? 👇
The Privacy Problem
Public permissionless blockchains are, well... PUBLIC. That means all your on-chain activity is stored for ever and for everyone to see on the blockchain. But with that transparency comes a lack of privacy. This introduces a number of risks to users:
⚠️ Theft: Criminals can see what you own, so they can easily target you and steal your crypto.
⚠️ Surveillance: Governments can surveil you, even if you use multiple addresses.
⚠️ MEV: Bots can front-run you, creating a hidden tax on every transaction.
How does HE work?
HE is a cryptographic tool that allows you to perform certain types of computations directly on the homomorphically encrypted ciphertext, generating the same results as if you performed the operations on the plaintext.
There are two types of HE: partially homomorphic encryption (PHE) & fully homomorphic encryption (FHE). PHE allows for a limited number of operations on the ciphertext (e.g. addition or multiplication), while FHE allows for any computation to be performed on the ciphertext and is hence the holy grail.
HE can significantly improve transaction confidentiality and user anonymity in public blockchain networks by allowing data to be encrypted and remain so even during computational processes.
To illustrate how FHE works, let's look at an example:
Suppose Alice wants to send Bob a message containing the result of a complex computation, but wants to keep the message private from any observers.
1️⃣ Alice and Bob agree on a set of parameters and an encryption scheme that allows for any computation to be performed on the ciphertext.
2️⃣ Alice generates a public key and private key, and sends the public key to Bob.
3️⃣ Alice encrypts the message (result of complex computation) using her private key and the agreed-upon encryption scheme, resulting in the ciphertext c.
4️⃣ Alice sends c to Bob.
5️⃣ Bob uses the public key to decrypt the ciphertext c and obtains the original message (result of complex computation).
Bob can verify the message is correct by performing the same computation and checking the result.
While FHE has limitations (e.g. limited efficiency, large ciphertext size, need for a trusted setup), it is expected to play an increasingly important role in the blockchain space in the coming years and could become a key enabler for privacy-requiring use cases.
Why does FHE matter for on-chain privacy?
Data included in transactions is encrypted and never visible to anyone. Also, states are updated while remaining encrypted at all times. Not even block producers can see the data. Finally, data stored on-chain remains encrypted end-to-end, even when used by smart contacts.
🔹 Trustless bridges: Use an encrypted key to sign bridge transactions homomorphically.
🔹 Blind auctions: Great for NFT auctions, RWAs, DeFi darkpools, marketplaces, etc...
🔹 Confidential voting: Keep choices and token amounts encrypted when voting.
🔹 FHE-rollups: Optimistic FHE rollups for general purpose computation are already possible, and ZK FHE rollups will be possible within ~3 years.
Taking FHE from 5 TPS to 1000+ TPS
While the use of HE is currently still scarce, it definitely bears great potential to improve user privacy across the blockchain space. With the expected FHE hardware accelerators until 2025, we could see FHE speed up by 1000x or more!
So prepare yourself, this might be the ZK of tomorrow in terms of hype!
And talking about ZK, the holy grail will be using the verifiable computation that zk proofs enable to scale, while having smart contracts perform computations over fully homomorphically encrypted data to enable private programmability!
Projects building with HE:
Maybe the leader in this space is @DarkFiSquad, that is building a private base layer for DeFi powered by HE & ZK tech!
Others are:
🔹 @DeroProject
🔹 @fhenix
That's a wrap for today! I hope you liked this short presentation! 🫡
Make sure to follow me @zerokn0wledge_ to stay up to date with the newest narratives and get airdropped daily alpha on modular scaling and privacy preserving technologies! 🥷 🪂
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