We study the following problem: A data distributor has given sensitive data to a set of supposedly trusted agents (third parties). Some of the data are leaked and found in an unauthorized place (e.g., on the web or somebody's laptop). The distributor must assess the likelihood that the leaked data came from one or more agents, as opposed to having been independently gathered by other means. We propose data allocation strategies (across the agents) that improve the probability of identifying leakages. These methods do not rely on alterations of the released data (e.g., watermarks). In some cases, we can also inject “realistic but fake” data records to further improve our chances of detecting leakage and identifying the guilty party.

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Data Leakage Detection

Digital watermarking for relational databases emerged as a candidate so- lution to provide copyright protection, tamper detection, traitor tracing, maintaining integrity of relational data. Many watermarking techniques have been proposed in the literature to address these purposes. In this paper, we survey the current state-of-the- art and we classify them according to their intent, the way they express the watermark, the cover type, the granularity level, and their verifiability.

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Watermarking Techniques for Relational Databases: Survey, Classification and Comparison

Over the last 25 years, there has been much work on multimedia digital watermarking. In this domain, the primary limitation to watermark strength has been in its visibility. For multimedia watermarks, invisibility is defined in human terms (that is, in terms of human sensory limitations). In this paper, we review recent developments in the non-media applications of data watermarking, which have emerged over the last decade as an exciting new sub-domain. Since by definition, the intended receiver should be able to detect the watermark, we have to redefine invisibility in an acceptable way that is often application-specific and thus cannot be easily generalized. In particular, this is true when the data is not intended to be directly consumed by humans. For example, a loose definition of robustness might be in terms of the resilience of a watermark against normal host data operations, and of invisibility as resilience of the data interpretation against change introduced by the watermark. In this paper, we classify the data in terms of data mining rules on complex types of data such as time-series, symbolic sequences, data streams, and so forth. We emphasize the challenges involved in non-media watermarking in terms of common watermarking properties, including invisibility, capacity, robustness, and security. With the aid of a few examples of watermarking applications, we demonstrate these distinctions and we look at the latest research in this regard to make our argument clear and more meaningful. As the last aim, we look at the new challenges of digital watermarking that have arisen with the evolution of big data.

On the Properties of Non-Media Digital Watermarking: A Review of State of the Art Techniques

Problem statement: Digital multimedia watermarking technology was suggested in the last decade to embed copyright information in digital objects such images, audio and video. However, the increasing use of relational database systems in many real-life applications created an ever increasing need for watermarking database systems. As a result, watermarking relational database systems is now merging as a research area that deals with the legal issue of copyright protection of database systems. Approach: In this study, we proposed an efficient database watermarking algorithm based on inserting binary image watermarks in non-numeric mutli-word attributes of selected database tuples. Results: The algorithm is robust as it resists attempts to remove or degrade the embedded watermark and it is blind as it does not require the original database in order to extract the embedded watermark. Conclusion: Experimental results demonstrated blindness and the robustness of the algorithm against common database attacks.

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Robust and Blind Watermarking of Relational Database Systems

We put forward a fragile zero watermarking scheme to detect and characterize malicious modifications made to a database relation. Most of the existing watermarking schemes for relational databases introduce intentional errors or permanent distortions as marks into the database original content. These distortions inevitably degrade the data quality and data usability as the integrity of a relational database is violated. Moreover, these fragile schemes can detect malicious data modifications but do not characterize the tempering attack, that is, the nature of tempering. The proposed fragile scheme is based on zero watermarking approach to detect malicious modifications made to a database relation. In zero watermarking, the watermark is generated (constructed) from the contents of the original data rather than introduction of permanent distortions as marks into the data. As a result, the proposed scheme is distortion-free; thus, it also resolves the inherent conflict between security and imperceptibility. The proposed scheme also characterizes the malicious data modifications to quantify the nature of tempering attacks. Experimental results show that even minor malicious modifications made to a database relation can be detected and characterized successfully.

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A Fragile Zero Watermarking Scheme to Detect and Characterize Malicious Modifications in Database Relations

As an embranchment of information hiding, the digital watermark techniques have been attracting more and more interests in both research and industrial fields. As a tool for storing and managing data, relational database is widely used in many information systems. It is a crucial issue to protect the copyright of relational data. In order to make watermarking information more intuitive and easier to identify, We propose a novel watermarking method, which embeds an image watermark into relational database. Experimental results verify the effectiveness of the proposed method.

Watermarking relational database using image

This paper studies an improved algorithm to watermark numeric attributes in relational databases for copyright protection. It reviews related researches and presents an improved insertion algorithm, a detection algorithm and a recover algorithm. We introduce a varied-size grouping method in our insertion algorithm to insert a meaningful watermark. We also introduce a new mechanism to insert watermarks using the mark itself to decide marked positions. This insertion mechanism can be validated in our detection algorithm to decide whether a watermark exists or not. A badly destroyed marked relation or only a small part of it could still be detected successfully. Our recover algorithm introduces a competing mechanism to help recover the exact meaningful watermark after the detection result confirms the existence of the watermark. The experiments show it's robust to various attacks.

An Improved Algorithm to Watermark Numeric Relational Data

An improved algorithm to watermark numeric relational data

Protection of digital assets from piracy has received increasing interests where sensitive, valuable data need to be released. This paper addresses the problem of watermarking spatial trajectory database. The formal definition of the problem is given and the potential attacks are analyzed. Then a novel watermarking method is proposed, which embed the watermark information by introducing a small error to the trajectory shape rather than certain data values. Experimental results justify the usefulness of the proposed method, and give some empirical conclusions on the parameter settings.

Watermarking spatial trajectory database

The invention relates to a method for embedding and extracting water spot from English text in the field of text copyright protection technique It has the following steps: changing the copyright information into binary bit string, reading in the text and filtering special characters and indent and then operating the character string and copyright person's private key to obtain integer number Z, if Z can divide embedding ratio exactly, the next sentence is water spot information sentence, using Z to do negation with copyright information binary bit string to ascertain the information bit of bided embedding water spot, using Z to do negation with the number of the characters of water spot information sentence to ascertain the location of the water spot information bit so that 0, 1 which can represent the relation of the adjacent alpha codes are uniform with bided embedding water spot information bit until finish text The process of extracting water spot information is a reverse process of embedding it

Zhihao Zhang

Papers

Watermarking relational database using image

An Improved Algorithm to Watermark Numeric Relational Data

An improved algorithm to watermark numeric relational data

Watermarking spatial trajectory database

Method for embedding and extracting watermark in English texts