In today’s digital landscape, where media content is rapidly shared and easily replicated, ensuring the authenticity and ownership of user-generated content is crucial. This paper presents a Certificate Authority (CA) system designed to validate and authenticate media content with the potential for seamless integration into social media platforms. The system ensures media authenticity by certifying user ownership through public key certification and implementing robust plagiarism detection techniques to prevent unauthorized content reuse. The public key certification process leverages a zero-knowledge proof challenge, securing user identity while verifying the legitimacy of their media content. To detect replicated or plagiarized content, the system employs advanced hashing techniques such as difference hashing, average hashing, perceptual hashing and vector embeddings. Additionally, the CA system incorporates human intervention to enhance the accuracy of the plagiarism detection process. Once media content passes these checks, it is signed using cryptographic signatures, which provide verifiable proof of authenticity and ownership that can be recognized across platforms.

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Media Certificate Authority: A System to Ensure Media Content Originality for Daily Lifelog Media Collection

  • Minh-Quan Ho-Le,
  • Duy-Khang Ho,
  • Minh-Triet Tran,
  • Mai-Khiem Tran

摘要

In today’s digital landscape, where media content is rapidly shared and easily replicated, ensuring the authenticity and ownership of user-generated content is crucial. This paper presents a Certificate Authority (CA) system designed to validate and authenticate media content with the potential for seamless integration into social media platforms. The system ensures media authenticity by certifying user ownership through public key certification and implementing robust plagiarism detection techniques to prevent unauthorized content reuse. The public key certification process leverages a zero-knowledge proof challenge, securing user identity while verifying the legitimacy of their media content. To detect replicated or plagiarized content, the system employs advanced hashing techniques such as difference hashing, average hashing, perceptual hashing and vector embeddings. Additionally, the CA system incorporates human intervention to enhance the accuracy of the plagiarism detection process. Once media content passes these checks, it is signed using cryptographic signatures, which provide verifiable proof of authenticity and ownership that can be recognized across platforms.