A Blockchain Solution for Decentralized Content Verification and its Application to Deepfake Detection and Fintech Credit Scoring
Abstract
This paper presents a blockchain-based framework for decentralized content verification, with two applied domains: detecting AI-generated deepfakes and automating credit scoring in the Fintech sector. The work introduces a hybrid on-chain/off-chain architecture where independent attesters score content off-chain and final outcomes are anchored on-chain for public auditability, forming the scientific foundation of the Attestia protocol.
Key topics
Key contributions
Hybrid Architecture
A novel on-chain/off-chain design where attesters score content independently off-chain, and final outcomes are anchored on-chain via the Ethereum Attestation Service (EAS) for public auditability.
Deepfake Detection Application
The framework is applied to AI-generated media detection, demonstrating how decentralized consensus can produce more reliable and tamper-resistant authenticity scores than centralized models.
Fintech Credit Scoring
A second application domain explores how the same decentralized verification infrastructure can automate and audit credit scoring processes in the financial sector, improving transparency and reducing bias.
Incentive & Slashing Mechanisms
A staking-based incentive model is formally described: attesters earn rewards aligned with consensus and face stake slashing for deviating scores, ensuring honest participation at protocol level.
Connection to Attestia
From research to protocol
Attestia is the direct productization of this research. The decentralized verification architecture, incentive mechanisms, and on-chain attestation design described in the paper are the technical backbone of the Attestia protocol running today on Base Sepolia.