In today’s digital era, it is very easy to copy, manipulate and distribute multimedia data over an open channel. Copyright protection, content authentication, identity theft, and ownership identification have become challenging issues for content owners/distributors. Off late data hiding methods have gained prominence in areas such as medical/healthcare, e-voting systems, military, communication, remote education, media file archiving, insurance companies, etc. Digital watermarking is one of the burning research areas to address these issues. In this survey, we present various aspects of watermarking. In addition, various classification of watermarking is presented. Here various state-of-the-art of multimedia and database watermarking is discussed. With this survey, researchers will be able to implement efficient watermarking techniques for the security of multimedia and database.

A Recent Survey on Multimedia and Database Watermarking

Digital videos are one of the most widespread forms of multimedia in day to day life. These are widely transferred over social networking websites such as Facebook, Instagram, WhatsApp, YouTube, etc. through the Internet. Availability of modern and easy to use editing tools have facilitated the modification of the contents of the digital videos. Therefore, it has become an essential concern for the legitimacy, trustworthiness, and authenticity of these digital videos. Digital video forgery detection aims to identify the manipulations in the video and to check its authenticity. These techniques can be divided into active and passive techniques. In this paper, a comprehensive survey on video forgery detection using passive techniques have been presented. The primary goal of this survey is to study and analyze the existing passive video forgery detection techniques. Firstly, the preliminary information required for understanding video forgery detection is presented. Later, a brief survey of existing passive video forgery detection techniques based on the features, forgery identified, datasets used, and performance parameters detail along with their limitations are reviewed. Then, anti-forensics strategy and deepfake detection in the video are discussed. After that, standard benchmark video forgery datasets and the generalized architecture for passive video forgery detection techniques are discussed. Finally, few open challenges in the field of passive video forgery detection are also described.

A comprehensive survey on passive techniques for digital video forgery detection

This paper presents passive blind forgery detection to identify frame duplication attack in Moving Picture Experts Group-4 (MPEG-4) video. In this attack, one or more frames are copied and pasted at other location in the same video to hide or highlight particular activity. Since the tampered frames are from the same video, their statistical properties are uniform, which makes challenging to identify duplicate frames. In this paper, a two-step algorithm is proposed, in which the suspicious frames are identified, their features are extracted and compared with other frames of the test video to take the decision. Scale Invariant Feature Transform (SIFT) key-points are used as feature for comparison. Finally, Random Sample Consensus algorithm is used to locate duplicate frames. The proposed method is tested on compressed and uncompressed videos with variable compression rate. The simulation results show that the proposed scheme is competent to detect the tampered frames with 99.8% average accuracy. Comparative analysis is made for the proposed method with existing methods with respect to parameters Precision Rate (PR), Recall Rate (RR), Detection Accuracy (DA). The average values of PR, RR, and DA for the proposed method are 99.9%, 99.7%, 99.8% respectively, which are better than other methods. The proposed method needs average 33 seconds of simulation time, which is less as compared to other methods.

A passive blind forgery detection technique to identify frame duplication attack

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.

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

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.

Semantic-driven watermarking of relational textual databases

In this paper, a new multi-attribute and high capacity image-based watermarking technique for relational data is proposed. The embedding process causes low distortion into the data considering the usability restrictions defined over the marked relation. The conducted experiments show the high resilience of the proposed technique against tuple deletion and tuple addition attacks. An interesting trend of the extracted watermark is analyzed when, within certain limits, if the number of embedded marks is small, the watermark signal far from being compromised, discretely improves in the case of tuple addition attacks. According to the results, marking 13% of the attributes and under an attack of 100% of tuples addition, 96% of the watermark is extracted. Also, while previous techniques embed up to 61% of the watermark, under the same conditions, we guarantee to embed 99.96% of the marks.

A Minimum Distortion: High Capacity Watermarking Technique for Relational Data

Watermarking techniques for relational data have been proposed to allow copyright protection and data authenticity, among other things. Almost all proposals depend on the primary key of the database relations for deciding where and how to place the marks. The primary key could be easily updated or deleted if the attacker does not require watermarked data to be placed back in the database. The few techniques trying to avoid this dependency create a virtual primary key through schemes that frequently compute non-unique values, which may cause watermark synchronization problems. Also, the deletion of attributes compromises obtaining same values for the virtual primary key used for the mark embedding. In this paper, we propose a solution that solves the dependency of the primary key, avoiding the problem of non-unique values and showing more resilience against attribute deletion attacks than previous schemes.

Maikel Lázaro Pérez Gort

Papers

A Minimum Distortion: High Capacity Watermarking Technique for Relational Data

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

Semantic-driven watermarking of relational textual databases

A Highly-Reliable Virtual Primary Key Scheme for Relational Database Watermarking Techniques

Temporal Copy-Move Forgery Detection and Localization Using Block Correlation Matrix