Query-preserving watermarking of relational databases and Xml documents

Author:

Gross-AMBLARD David1

Affiliation:

1. Le2i CNRS-U Bourgogne, DIJON CEDEX, France and INRIA Saclay, Paris

Abstract

Watermarking allows robust and unobtrusive insertion of information in a digital document. During the last few years, techniques have been proposed for watermarking relational databases or Xml documents, where information insertion must preserve a specific measure on data (for example the mean and variance of numerical attributes).In this article we investigate the problem of watermarking databases or Xml while preserving a set of parametric queries in a specified language, up to an acceptable distortion. We first show that unrestricted databases can not be watermarked while preserving trivial parametric queries. We then exhibit query languages and classes of structures that allow guaranteed watermarking capacity, namely 1) local query languages on structures with bounded degree Gaifman graph, and 2) monadic second-order queries on trees or treelike structures. We relate these results to an important topic in computational learning theory, the VC-dimension. We finally consider incremental aspects of query-preserving watermarking.

Funder

European Research Council

Publisher

Association for Computing Machinery (ACM)

Subject

Information Systems

Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An Improved Reversible Database Watermarking Method based on Histogram Shifting;Proceedings of the 2023 ACM Workshop on Information Hiding and Multimedia Security;2023-06-28

2. Reversible Database Watermarking Based on Order-preserving Encryption for Data Sharing;ACM Transactions on Database Systems;2023-05-13

3. Biometric Masking to Re-establish the Database Through Watermarking with Distortion Control;Algorithms for Intelligent Systems;2023

4. Empirical analysis of the impact of queries on watermarked relational databases;Expert Systems with Applications;2022-10

5. FBIPT: A New Robust Reversible Database Watermarking Technique Based on Position Tuples;2022 4th International Conference on Data Intelligence and Security (ICDIS);2022-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3