M.S. Candidate: Mustafa Zemin
Program: Information Systems
Date: 07.01.2025 / 14:00
Place: A-212

Abstract: The increasing popularity of deepfake technology is progressively posing a significant threat to information integrity and security. There are numerous solutions to the detect deepfakes, but they usually fail to detect all of the deepfakes generated by different technologies. This thesis aims to find a solution to detect deepfakes independent of its generation technique. This thesis proposes a Deepfake Detection System that leverages innovative solutions through public blockchain and collective intelligence. This paper 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 trustlessly counter digital misinformation.