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논문 기본 정보

자료유형
학술저널
저자정보
Md Mamunur Rashid (Pukyong National University) Suk-Hwan Lee (Donga University) Ki-Ryong Kwon (Pukyong National University)
저널정보
한국멀티미디어학회 멀티미디어학회논문지 멀티미디어학회논문지 제24권 제8호
발행연도
2021.8
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1,044 - 1,058 (15page)

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초록· 키워드

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Tempered electronic contents have multiplied in last few years, thanks to the emergence of sophisticated artificial intelligence(AI) algorithms. Deepfakes (fake footage, photos, speech, and videos) can be a frightening and destructive phenomenon that has the capacity to distort the facts and hamper reputation by presenting a fake reality. Evidence of ownership or authentication of digital material is crucial for combating the fabricated content influx we are facing today. Current solutions lack the capacity to track digital media"s history and provenance. Due to the rise of misrepresentation created by technologies like deepfake, detection algorithms are required to verify the integrity of digital content. Many real-world scenarios have been claimed to benefit from blockchain"s authentication capabilities. Despite the scattered efforts surrounding such remedies, relatively little research has been undertaken to discover where blockchain technology can be used to tackle the deepfake problem. Latest blockchain based innovations such as Smart Contract, Hyperledger fabric can play a vital role against the manipulation of digital content. The goal of this paper is to summarize and discuss the ongoing researches related to blockchain’s capabilities to protect digital content authentication. We have also suggested a blockchain (smart contract) dependent framework that can keep the data integrity of original content and thus prevent deepfake. This study also aims at discussing how blockchain technology can be used more effectively in deepfake prevention as well as highlight the current state of deepfake video detection research, including the generating process, various detection algorithms, and existing benchmarks.

목차

ABSTRACT
1. INTRODUCTION
2. RELATED WORKS AND STUDIES
3. RESEARCH METHODOLOGY
4. BLOCKCHAIN BACKGROUND
5. CREATION AND DETECTION OF DEEPFAKE
6. PROPOSED FRAMEWORK
7. IMPLEMENTATION AND EVALUATION
8. CONCLUSION
REFERENCE

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