The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Combating Deepfake Videos Using Blockchain and Smart Contracts
Open accessAbstract
With the rise of artificial intelligence (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. 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 source even if the digital content is copied multiple times. The smart contract utilizes the 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.
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“However, other researchers (Parikh and Atrey 2018; Fraga-Lamas and Fernández-Caramés 2020; Hasan and Salah 2019; Masciari et al. 2020; Bakdash et al. 2018; Elhadad et al. 2019; Yang et al. 2019b) focus on the content to categorize types of fake news through distinguishing the different formats and content types of data in the news (e.g., text and/or multimedia).”
From Fake news, disinformation and misinformation in social media: a review (2023) · cites this paper as Hasan and Salah 2019
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Additionally, a security analysis of their BC-based solution shows how it addresses important security objectives like integrity, accountability, authorization, availability, and non-repudiation.”
From Deepfakes: current and future trends (2024) · cites this paper as Hasan and Salah 2019
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“Their answer is based on the idea that content can be real and authentic if it can be reliably linked to a reliable or trustworthy source.”
From Deepfakes: current and future trends (2024) · cites this paper as Hasan and Salah 2019
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In the citing paper
“A scheme using BC-based Ethereum technology, the second largest BC network, specifically Ethereum smart contracts, to track the provenance and history of digital content to its original source, even if it is copied multiple times, is presented in Hasan and Salah (2019).”
From Deepfakes: current and future trends (2024) · cites this paper as Hasan and Salah 2019
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In the citing paper
“Leveraging technologies such as blockchain (Hasan and Salah 2019), or privacy-enhancing digital fi ngerprints can transparently trace content origins (Barrington et al. 2023).”
From Generative AI and deepfakes: a human rights approach to tackling harmful content (2024) · cites this paper as Hasan and Salah 2019
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In the citing paper
“Other meth- ods such as lip-syncing approaches [67–69] and im- age quality metrics with support vector machine (SVM) [70] produce very high error rate when applied to detect deepfake videos from this newly produced dataset.”
From Deep learning for deepfakes creation and detection: A survey (2022) · cites this paper as [68]
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Citations
Cites
Blockchains and smart contracts for the internet of things
Christidis, K., & Devetsikiotis, M. (2016) · IEEE Access · doi:10.1109/access.2016.2566339 · Cited by 4,552
MedRec: Using Blockchain for Medical Data Access and Permission Management
Azaria, A., Ekblaw, A., Vieira, T., & Lippman, A. (2016) · 2016 2nd International Conference on Open and Big Data (OBD) · doi:10.1109/obd.2016.11 · Cited by 2,526
IoT security: Review, blockchain solutions, and open challenges
Khan, M. A., & Salah, K. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2017.11.022 · Cited by 2,488
Self-citationExposing DeepFake Videos By Detecting Face Warping Artifacts
Li, Y., & Lyu, S. (2018) · arXiv · doi:10.48550/arxiv.1811.00656 · Cited by 785
Securing Smart Cities Using Blockchain Technology
Biswas, K., & Muthukkumarasamy, V. (2016) · 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc-smartcity-dss.2016.0198 · Cited by 601
A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things
Tian, F. (2017) · International Conference on Service Systems and Service Management · doi:10.1109/icsssm.2017.7996119 · Cited by 594
Toyoda, K., Mathiopoulos, P. T., Sasase, I., & Ohtsuki, T. O. (2017) · IEEE Access · doi:10.1109/access.2017.2720760 · Cited by 587
Blockchain Technology in Finance
Treleaven, P. C., Brown, R. G., & Yang, D. (2017) · Computer · doi:10.1109/mc.2017.3571047 · Cited by 587
Blockchain: Future of financial and cyber security
Singh, S., & Singh, N. (2016) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i.2016.7918009 · Cited by 272
Artificial Intelligence, Deepfakes and a Future of Ectypes
Floridi, L. (2018) · Philosophy & Technology · doi:10.1007/s13347-018-0325-3 · Cited by 203
Securing Video Integrity Using Decentralized Trusted Timestamping on the Bitcoin Blockchain
Gipp, B., Kosti, J., & Breitinger, C. (2016) · GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) · Cited by 48
Lelantos: A Blockchain-Based Anonymous Physical Delivery System
AlTawy, R., ElSheikh, M., Youssef, A., & Gong, G. (2017) · Conference on Privacy, Security and Trust · doi:10.1109/pst.2017.00013 · Cited by 44
Garlin Gilchrist: Fighting fake news and the information apocalypse
Stover, D. (2018) · Bulletin of the Atomic Scientists · doi:10.1080/00963402.2018.1486618 · Cited by 27
Research works printed but not linked: 16
- 2019, IPFS is the Distributed Web
- 2019, Optimizing your Solidity Contracts Gas Usage
- 2019, Are Deepfakes the New Fakenews?
- 2019, The Civil White Paper
- 2019, How Faking Videos Became EasyÂ?and why that’s so Scary
- 2019, ETH gas station
- 2019, Is your Certificate of Authenticity Worth the Paper it’s Printed on?
- 2019, What Counts as an Artwork Proof of Authenticity
- 2019, Lawmakers Warn of ‘Deepfake’ Videos Ahead of 2020 Elections
- 2019, Art Provenance What it is and How to Verify it
- 2019, When Seeing is no Longer Believing Inside the Pentagon’s Race Against Deepfake Videos
- 2019, Deepfake-Busting Apps can Spot Even a Single Pixel Out of Place
- 2019, Fight AI With AI! Code Taught to Finger Naughty Deepfake Vids Made by Machine-Learning Algos
- 2019, Authenticity Verification of User Generated Video Files
- 2019, Ethereum Name Service
- 2019, Originalmy Products
Cited by
Sorted by citations
The Emergence of Deepfake Technology: A Review
Westerlund, M. (2019) · Technology Innovation Management Review · doi:10.22215/timreview/1282 · Cited by 1,138
Media Forensics and DeepFakes: An Overview
Verdoliva, L. (2020) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2020.3002101 · Cited by 979
The Creation and Detection of Deepfakes: A Survey
Mirsky, Y., & Lee, W. (2022) · ACM Computing Surveys · doi:10.1145/3425780 · Cited by 863
The Creation and Detection of Deepfakes: A Survey
Mirsky, Y., & Lee, W. (2020) · arXiv · doi:10.48550/arxiv.2004.11138 · Cited by 863
Fake news, disinformation and misinformation in social media: a review
Aïmeur, E., Amri, S., & Brassard, G. (2023) · Social Network Analysis and Mining · doi:10.1007/s13278-023-01028-5 · Cited by 772
Metadata
- Authors
- Hasan, H. R., & Salah, K.
- Affiliations
- Khalifa University of Science and Technology (AE)
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 41596-41606
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2920877282
- Cited by
- 339
- References
- 13
- Citations by year
- 2026: 19 · 2025: 37 · 2024: 54 · 2023: 53 · 2022: 49 · 2021: 55 · 2020: 51 · 2019: 21
- FWCI
- 54.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Digital Media Forensic Detection
- Keywords
- deepfakes, video authenticity, blockchain, smart contracts, Ethereum, IPFS, content provenance
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