Abstract:

In today's digital era, the exponential growth of information across various domains has significantly transformed the way we access and share knowledge. With the increasing connectivity through the Internet, digital data has become a primary resource for information on virtually any topic. However, this surge in digital data accessibility has also led to the pervasive issue of plagiarism and the violation of intellectual proeprty rights (IPR), posing a substantial deterrent for individuals and institutions wishing to share their findings or data due to the fear of misuse and lack of proper compensation or recognition for their efforts. A robust solution to this problem is the implementation of digital watermarks, which serve as markers to enforce ownership rights and protect digital content.

Digital watermarking encompasses various algorithms designed to embed ownership information into digital data. These algorithms range from complex mathematical functions to concepts like genetic algorithms. In this paper, we present a reversible watermarking algorithm specifically tailored for semi-structured data and we demonstrate the potential and resilience of its decoding phase in combating data theft.

The primary focus of this paper is on a watermark decoding solution for semi-structured data within a blockchain-based marketplace. The proposed solution involves several key components, including preprocessing, watermark embedding and extraction, and the evaluation of watermarking results. The technical aspects delve into the specifics of decoding input, file parsing, and the overall decoding flow. Additionally, the user interface is designed to facilitate the creation of watermarked data sets and to test files for potential data forgery or theft.

The paper also addresses several critical issues identified in the watermarking process, such as the substantial alteration of numerical values in watermarked data, which can render the data obsolete and unmarketable. To mitigate this, the solution focuses on modifying only the floating-point numerical values, thereby minimizing the overall mutation of the original data. Moreover, the memory usage during the watermarking process is optimized through the implementation of efficient parsing mechanisms like data streams.

The technology stack chosen for this project includes a switch from Java to C# for the watermarking algorithms, leveraging the advantages of C# for code improvement and backend integration using ASP.NET Core. The frontend development utilizes frameworks like React, Vue, and Svelte, with the entire application designed to run locally on the client’s machine to ensure data privacy and security. For data storage, SQLite is used due to its lightweight and efficient handling of JSON data.

The results of this study highlight the effectiveness of the proposed watermarking solution in safeguarding semi-structured data against plagiarism and the violation of IRP. The combination of robust embedding and resilient decoding mechanisms ensures the integrity and ownership of digital content, making it a viable solution for protecting intellectual property in the digital age. The paper concludes with an emphasis on the potential applications of this watermarking technique in various fields and the importance of continued research to enhance data security measures.

Keywords:

Watermarking, intellectual property rights, blockchain.