project screenshot 1
project screenshot 2
project screenshot 3
project screenshot 4
project screenshot 5

AdFHE

FHE-based personalized advertising protocol: Displaying relevant ads while safeguarding user confidentiality.

AdFHE

Created At

ETHGlobal Brussels

Winner of

Fhenix - Best use of Fhenix Stack 3rd place

Hyperlane - Best Use of Hyperlane

The Graph - Best New Subgraph 3rd place

ETHGlobal - 🏆 ETHGlobal Brussels Finalist

Project Description

AdFHE enables personalized advertising by leveraging fully homomorphic encryption (FHE), a technology that allows computations to be performed on encrypted data without decrypting it. This means AdFHE can analyze user traits and preferences securely, ensuring privacy is maintained throughout the process. Much like how leading search engines and social media platforms deliver tailored content without compromising personal details, AdFHE utilizes a recommendation algorithm. This algorithm processes encrypted user data, enabling the platform to deliver targeted advertisements while safeguarding individual search histories and personal information. By prioritizing privacy and security through FHE, AdFHE sets a new standard in personalized advertising, ensuring users receive relevant ads without sacrificing confidentiality.

How it's Made

Advertisers sign up with their email address through Dynamic and pay a fee based on the duration they wish their ad to be active on Scroll and Zircuit. Since Scroll has a lot of liquidity and Zircuit is a ZK-rollup utilizing zkSNARKs for state validation, all data required for proof construction is published on Ethereum L1. The advertisements are then transmitted to Fhenix using cross-chain messaging via Hyperlane.

When users input their data into the protocol (similar to how Google collects information based on searches), the data is encrypted and stored in the contract. When a user visits a webpage using our protocol for advertisements, an on-chain matrix multiplication matches advertisements with users' encrypted personal data. This approach allows for displaying ads relevant to users' interests without revealing any confidential information.

Our decentralized subgraph, deployed using The Graph, enables effective filtering of advertisement data.

background image mobile

Join the mailing list

Get the latest news and updates