Distortion-free Watermarking Scheme for Compressed Data in Columnar Database

Yaqub, Waheeb; Kamel, Ibrahim; Aung, Zeyar

doi:10.5220/0006857203430353

Cited by 5 publications

(3 citation statements)

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“…The proposal in [73] generates an image as a watermark from the database content. In [74], each column (attribute) is organized into groups, each having g data elements. The data elements in each group are re-ordered based on a watermark value.…”

Section: E: Othersmentioning

confidence: 99%

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Rani

Halder

2022

IEEE Access

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Digital watermarking is considered one of the most promising techniques to verify the authenticity and integrity of digital data. It is used for a wide range of applications, e.g., copyright protection, tamper detection, traitor tracing, maintaining the integrity of data, etc. In the past two decades, a wide range of algorithms for relational database watermarking has been proposed. Even though a number of surveys exist in the literature, they are unable to provide insightful guidance to choose the right watermarking technique for a given application. In this paper, we provide an exhaustive empirical study and thorough comparative analysis of various relational database watermarking techniques in the literature. Our work is different from the existing survey papers as we consider both distortion-based and distortion-free techniques along with a rigorous experimental analysis demonstrating a detailed comparison on robustness, data usability, and computational cost with considerable empirical evidence. INDEX TERMSDigital watermarking, relational database, empirical study, robustness, data usability. RAJU HALDER (Member, IEEE) received the Ph.D. degree from Università Ca´Foscari, Italy, in 2012. He is currently an Associate Professor with the Department of Computer Science and Engineering, IIT Patna. Before joining IIT Patna, he worked as a Postdoctoral Researcher with Macquarie University, Australia. He worked with the Robotics Team at HASLab (University of Minho), Portugal, in 2016. Prior to his Ph.D. degree, he had also worked as an Associate System Engineer at IBM India Private Ltd., from 2007 to 2008. His research interests include formal methods, blockchain technology, program analysis and verification, and data privacy and security.

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Section: E: Othersmentioning

confidence: 99%

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Rani

Halder

2022

IEEE Access

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“…This paper is a significantly extended and improved version of the conference paper 41 by the same authors, which is in turn based on the master's thesis 42 of the first author.…”

Section: Acknowledgmentsmentioning

confidence: 99%

Toward watermarking compressed data in columnar database architectures

Yaqub¹,

Kamel

Aung

2019

Security and Privacy

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A digital watermark is a secret pattern of bits inserted in the data objects to verify the integrity of the contents or to identify ownership. It is an effective technique for protecting various databases against data copyright infringement, piracy, and data tampering in both relational and not-only-Structured Query Language (NoSQL) databases including columnar database. Unfortunately, most of the existing digital watermarking schemes do not take into consideration the side effects that watermarking might have on the database's important characteristics such as data compression and overall performance. Thus, we are in need of database watermarking schemes that are tailored to the target database systems' specific architecture so that it does not interfere with the database's characteristics and performance. Columnar database is a type of NoSQL database where its data are stored in a column-wise manner. This facilitates better query processing (by leaving the unrelated attributes on the disk) as well as higher compression ratio. In this research, we propose a distortion-free fragile watermarking scheme for the columnar database architecture without interfering its underlying data compression scheme and its overall performance. The proposed scheme is flexible and can be adapted to various distributions of data. We tested our proposed scheme on both synthetic and real-world data, and proved its effectiveness.

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“…at is, they do not allow original data recovering from the watermarked relation [1][2][3][4]. erefore, although some distortion-free schemes exist in the literature [1][2][3][4][5][6][7][8][9], there is a need to develop a new generation of watermarking techniques that could efficiently address the abovementioned issues. To achieve that, reversible or lossless digital watermarking has been extended from multimedia assets to relational data to allow original data recovery at watermark detection.…”

Section: Introductionmentioning

confidence: 99%

Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion

Hamadou

Camara

Hassane

et al. 2020

Mathematical Problems in Engineering

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The protection of database systems content using digital watermarking is nowadays an emerging research direction in information security. In the literature, many solutions have been proposed either for copyright protection and ownership proofing or integrity checking and tamper localization. Nevertheless, most of them are distortion embedding based as they introduce permanent errors into the cover data during the encoding process, which inevitably affect data quality and usability. Since such distortions are not tolerated in many applications, including banking, medical, and military data, reversible watermarking, primarily designed for multimedia content, has been extended to relational databases. In this article, we propose a novel prediction-error expansion based on reversible watermarking strategy, which not only detects and localizes malicious modifications but also recovers back the original data at watermark detection. The effectiveness of the proposed method is proved through rigorous theoretical analysis and detailed experiments.

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Distortion-free Watermarking Scheme for Compressed Data in Columnar Database

Cited by 5 publications

References 0 publications

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Toward watermarking compressed data in columnar database architectures

Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion

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