Swathi Melkundi

Bio: Swathi Melkundi is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 1, co-authored 1 publications receiving 14 citations.

A robust technique for relational database watermarking and verification

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.

A Survey of Data Distortion Watermarking 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.

HQR-Scheme: A High Quality and resilient virtual primary key generation approach for watermarking relational data

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.

Semantic-driven watermarking of relational textual databases

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.