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Implementation of Blockchain Technology for Image Plagiarism Detection Using DCT, AES128, and SHA-1 Algorithms Duran, Filbert; Leonardo; Shickhem; Yennimar
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1205

Abstract

Plagiarism encompasses the act of appropriating high-quality user-generated content as if it were one's own intellectual property. Image plagiarism can be conceptualized as a broader category that encompasses the challenges of detecting copied images. Identifying instances of plagiarism is of paramount importance not only for graphic designers, professional photographers, and bloggers but also for publishing entities and legal practitioners seeking to uncover unauthorized reproductions of their creations. In addressing this issue, the implementation of blockchain technology presents a viable solution. Fundamentally more than just a collection of interconnected blocks, blockchain is characterized by the systematic recording of digital signatures or hashes of each block. Blockchain is essentially more than just a collection of interconnected blocks; it is characterized by the systematic recording of a digital signature or hash of each block. To generate the hash, cryptographic methods can be applied. This study aims to develop a web-based application that is adept at detecting image plagiarism through the application of blockchain technology. Images submitted by users will undergo plagiarism detection by an application that uses blockchain methodology. This study applies the DCT method to extract features from images, then uses the AES-128 and SHA-1 methods to generate blockchain. The results of this study are in the form of a website that can be used to detect image plagiarism. From the results of the tests carried out, it was obtained that the combination of the DCT, AES-128 and SHA-1 methods can detect image plagiarism with an accuracy of 100%. This means that the combination of these methods can be applied to carry out the process of detecting image plagiarism with a very high level of accuracy.