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Proceedings ArticleDOI

A robust technique for relational database watermarking and verification

TL;DR: This paper proposes a new watermarking technique, which will watermark both textual and numerical data and does watermark verification where, the watermark extracted from the database is compared with the original watermark that is known only to the owner of the database.
Abstract: Outsourcing of data is increasing with the rapid growth of internet. There is every possibility that data reaches illegal hands. As a result, there is increase in illegal copying of data, piracy, illegal redistribution, forgery and theft. Watermarking technology is a solution for these challenges. It addresses the ownership problem. It deters illegal copying and protects copyright of data. Watermarking technology mainly involves the process of watermark insertion and watermark extraction. Watermark insertion means embedding an imperceptible watermark in the relational database. In watermark extraction we extract the embedded watermark without the help of original database. In this paper we propose a new watermarking technique, which will watermark both textual and numerical data. Our proposed method also does watermark verification where, the watermark extracted from the database is compared with the original watermark that is known only to the owner of the database. This is accomplished through Levenshtein distance algorithm.
Citations
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Journal ArticleDOI
TL;DR: A review of data exfiltration attack vectors and countermeasures revealed that most of the state of the art is focussed on preventive and detective countermeasures and significant research is required on developing investigative countermeasures that are equally important.

76 citations


Cites background or methods from "A robust technique for relational d..."

  • ...[162] At rest A technique for watermarking textual data in relational database Melkundi & Chandandkhede [163] At rest A technique for watermarking both textual and numeric data in a relational database...

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  • ...Melkundi and Chandandkhede [163] proposes a watermarking technique for watermarking both textual and numeric data in a relational database to address the issue of data ownership and copyright....

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  • ...Our review reveals that a number of countermeasures ([39], [43], [45], [68], [86], [91], [99], [128], [163], [174], [177], [173] ) require manual efforts during deployment and operations such as (a) having a dedicated network administrator to promote a node from one security zone to another based on the sensitivity of the node [43]; (b) involvement of user for approval of each single data transfer out of user’s computer [68]; (c) manual addition of dummy records to the database for cyber deception [86]; (d) manually dividing a single table into several tables [91]; (e) involvement of expert investigators for manually gathering evidence of data leakage to identify the data leaker [174]; (f) manual writing of rules regarding sensitive data [173]; and (g) semi-automatic deployments [39]....

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Journal ArticleDOI
TL;DR: The experimental results show that the proposed approach outperforms existing solutions in detecting six families of malware: the detection accuracy of Sub-Curve HMM is over 94% compared to 83% for the baseline HMM approach and 73% for Information Gain.

18 citations

Journal ArticleDOI
TL;DR: This paper defines a new requirement analysis for data distortion watermarking relational databases and uses it to analyze important and newest research of data distort watermarked relational databases.
Abstract: Watermarking relation al database is a technique which can provide ownership protection and temper proofing for relational databases. Although it has been developed over ten years, it is still not popular. For attracting more people to study this technique, we introduce it in detail in this paper. The main contributions of this paper include: 1) To the best of our knowledge, this is the first paper which specially surveys data distortion watermarking relational databases; 2) We define a new requirement analysis t able for data distortion watermarking relational databases and use it to analyze important and t he newest research of data distortion watermarking relational databases; 3) We explain background knowledge of watermarking relational databases, such as types of attacks, requirements, and basic techniques.

14 citations


Cites background or methods from "A robust technique for relational d..."

  • ...Table 7: The requirement analysis of MelkundiChandankhede’s scheme [21]...

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  • ...[21], all belong to data distortion watermarking relational databases....

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  • ...The technique proposed by Swathi Melkundi and Chaitali Chandankhede [21]....

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Journal ArticleDOI
TL;DR: The metrics are introduced to allow precise measuring of the quality of the VPKs generated by any scheme without requiring to perform the watermark embedding, so that time waste can be avoided in case of low-quality detection.
Abstract: Most of the watermarking techniques designed to protect relational data often use the Primary Key (PK) of relations to perform the watermark synchronization. Despite offering high confidence to the watermark detection, these approaches become useless if the PK can be erased or updated. A typical example is when an attacker wishes to use a stolen relation, unlinked to the rest of the database. In that case, the original values of the PK lose relevance, since they are not employed to check the referential integrity. Then, it is possible to erase or replace the PK, compromising the watermark detection with no need to perform the slightest modification on the rest of the data. To avoid the problems caused by the PK-dependency some schemes have been proposed to generate Virtual Primary Keys (VPK) used instead. Nevertheless, the quality of the watermark synchronized using VPKs is compromised due to the presence of duplicate values in the set of VPKs and the fragility of the VPK schemes against the elimination of attributes. In this paper, we introduce the metrics to allow precise measuring of the quality of the VPKs generated by any scheme without requiring to perform the watermark embedding. This way, time waste can be avoided in case of low-quality detection. We also analyze the main aspects to design the ideal VPK scheme, seeking the generation of high-quality VPK sets adding robustness to the process. Finally, a new scheme is presented along with the experiments carried out to validate and compare the results with the rest of the schemes proposed in the literature.

12 citations


Cites background from "A robust technique for relational d..."

  • ...Based on that assumption, the majority of watermarking techniques proposed to protect relational data are PK-dependent (e.g. Franco-Contreras et al., 2014; İmamoğlu et al., 2015; Kamran et al., 2013; Melkundi and Chandankhede, 2015; Pérez Gort et al., 2017b)....

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  • ...Since it was published, the AHK algorithm has become the main model followed for PK-dependent techniques, which constitute the majority of watermarking techniques for relational data....

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  • ...Based on that assumption, the majority of watermarking techniques proposed to protect relational data are PK-dependent (e.g. Franco-Contreras et al., 2014; İmamoğlu et al., 2015; Kamran et al., 2013; Melkundi and Chandankhede, 2015; Pérez Gort et al., 2017b)....

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Journal ArticleDOI
TL;DR: A semantic-driven watermarking approach of relational textual databases is proposed, which marks multi-word textual attributes, exploiting the synonym substitution technique for text water marking together with notions in semantic similarity analysis, and dealing with the semantic perturbations provoked by the watermark embedding.
Abstract: In relational database watermarking, the semantic consistency between the original database and the distorted one is a challenging issue which is disregarded by most watermarking proposals, due to the well-known assumption for which a small amount of errors in the watermarked database is tolerable. We propose a semantic-driven watermarking approach of relational textual databases, which marks multi-word textual attributes, exploiting the synonym substitution technique for text watermarking together with notions in semantic similarity analysis, and dealing with the semantic perturbations provoked by the watermark embedding. We show the effectiveness of our approach through an experimental evaluation, highlighting the resulting capacity, robustness and imperceptibility watermarking requirements. We also prove the resilience of our approach with respect to the random synonym substitution attack.

11 citations

References
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DOI
06 Mar 2002
TL;DR: This standard describes a keyed-hash message authentication code (HMAC), a mechanism for message authentication using cryptographic hash functions, which can be used with any iterative FIPS-approved cryptographic hash function, in combination with a shared secret key.
Abstract: This standard describes a keyed-hash message authentication code (HMAC), a mechanism for message authentication using cryptographic hash functions. HMAC can be used with any iterative FIPS-approved cryptographic hash function, in combination with a shared secret key. The cryptographic strength of HMAC depends on the properties of the underlying hash function. The HMAC specification in this standard is a generalization of Internet RFC 2104, HMAC, Keyed-Hashing for Message Authentication, and ANSI X9.71, Keyed Hash Message Authentication Code.

388 citations

Book ChapterDOI
Rakesh Agrawal1, Jerry Kiernan1
20 Aug 2002
TL;DR: The need for watermarking database relations to deter their piracy, identify the unique characteristics of relational data which pose new challenges for water marking, and provide desirable properties of a watermarked system for relational data are enunciated.
Abstract: We enunciate the need for watermarking database relations to deter their piracy, identify the unique characteristics of relational data which pose new challenges for watermarking, and provide desirable properties of a watermarking system for relational data. A watermark can be applied to any database relation having attributes which are such that changes in a few of their values do not affect the applications. We then present an effective watermarking technique geared for relational data. This technique ensures that some bit positions of some of the attributes of some of the tuples contain specific values. The tuples, attributes within a tuple, bit positions in an attribute, and specific bit values are all algorithmically determined under the control of a private key known only to the owner of the data. This bit pattern constitutes the watermark. Only if one has access to the private key can the watermark be detected with high probability. Detecting the watermark neither requires access to the original data nor the watermark. The watermark can be detected even in a small subset of a watermarked relation as long as the sample contains some of the marks. Our extensive analysis shows that the proposed technique is robust against various forms of malicious attacks and updates to the data. Using an implementation running on DB2, we also show that the performance of the algorithms allows for their use in real world applications.

382 citations

Book
01 Jan 2003
TL;DR: Disclaimer These charts are provided as the online reference to the character contents of the Unicode Standard, Version 8.0 but do not provide all the information needed to fully support individual scripts using the Unicode standard.

188 citations

Journal ArticleDOI
TL;DR: This paper presents a mechanism for proof of ownership based on the secure embedding of a robust imperceptible watermark in relational data and formulate the watermarking of relational databases as a constrained optimization problem and discusses efficient techniques to solve the optimizationproblem and to handle the constraints.
Abstract: Proving ownership rights on outsourced relational databases is a crucial issue in today's internet-based application environments and in many content distribution applications In this paper, we present a mechanism for proof of ownership based on the secure embedding of a robust imperceptible watermark in relational data We formulate the watermarking of relational databases as a constrained optimization problem and discuss efficient techniques to solve the optimization problem and to handle the constraints Our watermarking technique is resilient to watermark synchronization errors because it uses a partitioning approach that does not require marker tuples Our approach overcomes a major weakness in previously proposed watermarking techniques Watermark decoding is based on a threshold-based technique characterized by an optimal threshold that minimizes the probability of decoding errors We implemented a proof of concept implementation of our watermarking technique and showed by experimental results that our technique is resilient to tuple deletion, alteration, and insertion attacks

135 citations


"A robust technique for relational d..." refers methods in this paper

  • ...The method proposed in [8] uses a partitioning approach that does not require marker tuple....

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