FACILITATING COLLABORATIVE DEEPFAKE DETECTION BASED ON BLOCKCHAIN TECHNOLOGY AND REPUTATION

Date

2025-1-07

Author

Zemin, Mustafa

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The increasing popularity of deepfake technology is progressively posing a significant threat to information integrity and security. There are numerous solutions to detect deepfakes, but they usually fail to detect all of the deepfakes generated by different technologies. This thesis aims to facilitate to detect deepfakes independent of their generation methods. This thesis proposes a Deepfake Detection System that leverages innovative solutions through public blockchain and collective intelligence. This thesis uses smart contracts on the Ethereum blockchain to provide a secure, decentralized way of verifying media content, ensuring an auditable and tamper-resistant framework. It integrates concepts of electronic voting to enable a network of participants to assess the authenticity of content through consensus mechanisms. This community-driven model is decentralized, enhancing detection accuracy while preventing single points of failure. Test results prove that the system is robust, reliable, and can scale deepfake detection for sustainable ways of combating digital misinformation. The proposed solution enhances deepfake detection capabilities and provides a framework for applying blockchain-based collaboration in other domains facing similar verification challenges to safely and trustless counter digital misinformation.

Subject Keywords

Deepfake Detection, Public Blockchain, Electronic Voting, Collective Intelligence, Ethereum

URI

https://hdl.handle.net/11511/113407

Collections

Graduate School of Informatics, Thesis