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Combating Deepfake Videos Using Blockchain and Smart Contracts


Scalable and Secure Big Data I

A Wavelet-Predominant Algorith

Class Agnostic Image Common Ob
Abstract


With the rise of AI and deep learning techniques, fake digital contents have proliferated in recent years. Fake footage, images, audios, and videos (known as deepfakes) can be a scary and dangerous phenomenon, and can have the potential of altering the truth and eroding trust by giving false reality. A Proof of Authenticity (PoA) of digital media is critical to help eradicate the epidemic of forged content. Current solutions lack the ability to provide history tracking and provenance of digital media. In this paper, we provide a solution and a general framework using Ethereum smart contracts to trace and track the provenance and history of digital content to its original sourceā??even if the digital content is copied multiple times. The smart contract utilizes hashes of the InterPlanetary File System (IPFS) used to store digital content and its metadata. Our solution focuses on video content, but the solution framework provided in this paper is generic enough and can be applied to any other form of digital content. Our solution relies on the principle that if the content can be credibly traced to a trusted or reputable source, the content can then be real and authentic. The full code of the smart contract has been made publicly available at Github.

KeyWords
AI, Deepfake, Blockchain, Ethereum, Smart Contracts



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