Decentralized Deepfake Detection Blockchain Network using Dynamic Algorithm management

TL;DR

This paper proposes a blockchain-based decentralized framework that combines deep learning and smart contracts to improve the detection and verification of deepfakes, enhancing digital media integrity.

Contribution

It introduces a novel decentralized system integrating dynamic algorithm management and token incentives for robust deepfake detection.

Findings

Enhanced trustless verification environment

Dynamic algorithm management improves adaptability

Blockchain ensures transparency and immutability

Abstract

Deepfake technology is a major threat to the integrity of digital media. This paper presents a comprehensive framework for a blockchain-based decentralized system designed to tackle the escalating challenge of digital content integrity. The proposed system integrates advanced deep learning algorithms with the immutable and transparent nature of blockchain technology to create a trustless environment where authenticity can be verified without relying on a single centralized authority. Furthermore, the system utilizes smart contracts for dynamic algorithm management and token-based incentives further enhances the system's effectiveness and adaptability. The decentralized architecture of the system democratizes the process of verifying digital content and introduces a novel approach to combat deepfakes. The collaborative and adjustable nature of this system sets a new benchmark for digital media integrity, offering a more robust digital media environment.