arXiv
Decentralized Deepfake Detection Blockchain Network using Dynamic Algorithm management
Dipankar Sarkar
Abstract
This paper presents a novel approach to deepfake detection through a decentralized blockchain network that dynamically manages detection algorithms. The system leverages blockchain technology to create a transparent and secure platform where multiple deepfake detection algorithms can be deployed, evaluated, and updated in real-time, ensuring adaptability to new deepfake techniques.
Summary
The rapid advancement of deepfake technology poses significant challenges to digital media authenticity. Our research introduces a blockchain-based solution that:
- Implements a decentralized network for deepfake detection
- Provides dynamic algorithm management capabilities
- Ensures transparent evaluation and updating of detection methods
- Creates a collaborative environment for researchers and developers
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Frequently Asked Questions
What is the Decentralized Deepfake Detection Blockchain Network?
The Decentralized Deepfake Detection Blockchain Network is a novel approach to deepfake detection that uses a blockchain-based network to dynamically manage detection algorithms. The system creates a transparent and secure platform where multiple deepfake detection algorithms can be deployed, evaluated, and updated in real-time, ensuring adaptability to new deepfake techniques. Published November 2023 on arXiv (2311.18545). 7 citations as of 2026.
How does the network stay ahead of new deepfake techniques?
The blockchain-based architecture allows multiple detection algorithms to be deployed, evaluated, and updated in real-time on the network. New algorithms can be added as they are developed; underperforming ones can be deprecated. The blockchain provides a transparent audit trail of which algorithm flagged which content. This is fundamentally different from monolithic deepfake detection systems that ship a single model.
Who is this paper for?
The paper is for: deepfake detection researchers, content authenticity / provenance researchers, blockchain infrastructure teams, social media platforms concerned about content integrity, and security researchers studying media manipulation. It is also relevant to policy makers thinking about content authenticity regulation.