Semi-structured data protection scheme based on robust watermarking

Abstract

Semi-structured data is a widely used text format for data interchange and storage. This paper proposes a robust watermarking scheme of data protection for semi-structured data, which uses JSON format as an example for illustration. We first parse JSON file into a data structure of distinct pairs. Afterwards, we generate a transfer matrix to get the intermediate sequences, which are then encoded using error-correction codes and embedded into the pairs. A private key is shared by the data hider and the recipient to resist collusion attacks. On the recipient's side, data extraction can be successfully carried out even the received stego data are tampered. The imperceptibility is realized by embedding data into the less significant digits of numeric data in the cover file. The proposed scheme can be extended on several other formats. The experimental results show that the proposed scheme is robust to various kinds of typical attacks such as contextual truncating, modification, and redundancy addition.

Reducing Multiple Occurrences of Meta-Mark Selection in Relational Data Watermarking

“…On the contrary, distortionfree techniques aim to preserve the integrity of the protected data [53], [54]. Usually, distortion-free techniques are defined as fragile, while distortion-based as robust approaches, to the extent that the embedded information survives at malicious or accidental attempts to remove it [1], [55]. Relational watermarking techniques can also be classified by their (i) cover-type, defining the type of data of the attribute in R selected to embed the marks; (ii) intent, i.e., ownership protection [1]- [3], [56], data tampering detection [4], [5], [57], traitor tracing [58]- [62], among others; (iii) watermark source, which can be meaningless such as a random binary stream [19], [31], or meaningful, i.e., a source for watermark generation presenting a meaning that does not depend on the watermarking technique [17], [64], [65].…”

Smardy: Zero-Trust FAIR Marketplace for Research Data

“…Watermarking uses broadly used file formats, such as CSV and JSON. Starting from this point, we decided to use a semistructured data protection scheme based on robust watermarking [22]. Since the main scope of this technique is to keep the data intact, this schema keeps the distortion of data relatively small.…”