Felix Fernandez-Pena

Bio: Felix Fernandez-Pena is an academic researcher. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 1, co-authored 2 publications receiving 4 citations.

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.

A Double Fragmentation Approach for Improving Virtual Primary Key-Based Watermark Synchronization

Abstract: Relational data watermarking techniques using virtual primary key schemes try to avoid compromising watermark detection due to the deletion or replacement of the relation’s primary key. Nevertheless, these techniques face the limitations that bring high redundancy of the generated set of virtual primary keys, which often compromises the quality of the embedded watermark. As a solution to this problem, this paper proposes double fragmentation of the watermark by using the existing redundancy in the set of virtual primary keys. This way, we guarantee the right identification of the watermark despite the deletion of any of the attributes of the relation. The experiments carried out to validate our proposal show an increment between 81.04% and 99.05% of detected marks with respect to previous solutions found in the literature. Furthermore, we found out that our approach takes advantage of the redundancy present in the set of virtual primary keys. Concerning the computational complexity of the solution, we performed a set of scalability tests that show the linear behavior of our approach with respect to the processes runtime and the number of tuples involved, making it feasible to use no matter the amount of data to be protected.

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.

Fingerprinting of Relational Databases for Stopping the Data Theft

Abstract: The currently-emerging technology demands sharing of data using various channels via the Internet, disks, etc. Some recipients of this data can also become traitors by leaking the important data. As a result, the data breaches due to data leakage are also increasing. These breaches include unauthorized distribution, duplication, and sale. The identification of a guilty agent responsible for such breaches is important for: (i) punishing the culprit; and (ii) preventing the innocent user from accusation and punishment. Fingerprinting techniques provide a mechanism for classifying the guilty agent from multiple recipients and also help to prevent the innocent user from being accused of the data breach. To those ends, in this paper, a novel fingerprinting framework has been proposed using a biometric feature as a digital mark (signature). The use of machine learning has also been introduced to make this framework intelligent, particularly for preserving the data usability. An attack channel has also been used to evaluate the robustness of the proposed scheme. The experimental study was also conducted to demonstrate that the proposed technique is robust against several malicious attacks, such as subset selection attacks, mix and match attacks, collusion attacks, deletion attacks, insertion attacks, and alteration attacks.

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Abstract: 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.

Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study

Abstract: 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.

A Double Fragmentation Approach for Improving Virtual Primary Key-Based Watermark Synchronization

Abstract: Relational data watermarking techniques using virtual primary key schemes try to avoid compromising watermark detection due to the deletion or replacement of the relation’s primary key. Nevertheless, these techniques face the limitations that bring high redundancy of the generated set of virtual primary keys, which often compromises the quality of the embedded watermark. As a solution to this problem, this paper proposes double fragmentation of the watermark by using the existing redundancy in the set of virtual primary keys. This way, we guarantee the right identification of the watermark despite the deletion of any of the attributes of the relation. The experiments carried out to validate our proposal show an increment between 81.04% and 99.05% of detected marks with respect to previous solutions found in the literature. Furthermore, we found out that our approach takes advantage of the redundancy present in the set of virtual primary keys. Concerning the computational complexity of the solution, we performed a set of scalability tests that show the linear behavior of our approach with respect to the processes runtime and the number of tuples involved, making it feasible to use no matter the amount of data to be protected.