Inspiration
We were inspired by the rapid rise of AI-generated content and aimed to create a solution that preserves authenticity in digital media.
What it does
DeFaux meant to be a secure database that potentially the whole Internet could use. Users upload their trustworthy data (as for now, we only hope their data is trustworthy, as we didn't implement any detection system just yet) to encrypt it with a code that we can recognize. Images can later be verified by reuploading, where we'll check if the code is unaltered and exists at all. Think of DeFaux as a prototype for a trustworthy Internet-wide resource.
How we built it
We combined a React frontend, MongoDB database, and Solidity-based blockchain to securely analyze, verify, and then store results.
Challenges we ran into
Integrating the blockchain smart contract with our MongoDB system was complex, and implementing clean routing in React also proved difficult.
Accomplishments that we're proud of
We met our core objectives—detecting AI-generated content and recording validations on a tamper-proof ledger—within the hackathon's tight deadline.
What we learned
We deepened our React skills, gained hands-on experience in blockchain development with Solidity, and refined our teamwork under pressure.
What's next for DeFaux Data Detector
The much more ambitious part of this project would be filtering out actual tampered data for the user, that was just out of scope for this group on a short deadline. We imagine DDD being the go-to resource for validating content online.
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