Watermarking security

International audienceThis chapter deals with applications where watermarking is a security primitive included in a larger system protecting the value of multimedia content. In this context, there might exist dishonest users, in the sequel so-called attackers, willing to read/overwrite hidden messages or simply to remove the watermark signal.The goal of this section is to play the role of the attacker. We analyze means to deduce information about the watermarking technique that will later ease the forgery of attacked copies. This chapter first proposes a topology of the threats in Section 6.1, introducing three different concepts: robustness, worst-case attacks, and security. Previous chapter has already discussed watermark robustness. We focus on worst-case attacks in Section 6.2, on the way to measure watermarking security in Section 6.3, and on the classical tools to break a watermarking scheme in Section 6.4. This tour of watermarking security concludes by a summary of what we know and still do not know about it (Section 6.5) and a review of oracle attacks (Section 6.6). Last, Section 6.7 deals with protocol attacks, a notion which underlines the illusion of security that a watermarking primitive might bring when not properly used in some applications

Steganalysis of video sequences using collusion sensitivity

In this thesis we present an effective steganalysis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this thesis we present methods that overcome this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. In particular we target the spread spectrum steganography method because of its widespread use. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking and more sophisticated pattern recognition tools. Through analysis and simulations we, evaluate the effectiveness of the video steganalysis method based on averaging based collusion scheme. Other forms of collusion attack in the form of weighted linear collusion and block-based collusion schemes have been proposed to improve the detection performance. The proposed steganalsyis methods were successful in detecting hidden watermarks bearing low SNR with high accuracy. The simulation results also show the improved performance of the proposed temporal based methods over the spatial methods. We conclude that the essence of future video steganalysis techniques lies in the exploitation of the temporal redundancy

Digital watermark technology in security applications

With the rising emphasis on security and the number of fraud related crimes around the world, authorities are looking for new technologies to tighten security of identity. Among many modern electronic technologies, digital watermarking has unique advantages to enhance the document authenticity. At the current status of the development, digital watermarking technologies are not as matured as other competing technologies to support identity authentication systems. This work presents improvements in performance of two classes of digital watermarking techniques and investigates the issue of watermark synchronisation. Optimal performance can be obtained if the spreading sequences are designed to be orthogonal to the cover vector. In this thesis, two classes of orthogonalisation methods that generate binary sequences quasi-orthogonal to the cover vector are presented. One method, namely "Sorting and Cancelling" generates sequences that have a high level of orthogonality to the cover vector. The Hadamard Matrix based orthogonalisation method, namely "Hadamard Matrix Search" is able to realise overlapped embedding, thus the watermarking capacity and image fidelity can be improved compared to using short watermark sequences. The results are compared with traditional pseudo-randomly generated binary sequences. The advantages of both classes of orthogonalisation inethods are significant. Another watermarking method that is introduced in the thesis is based on writing-on-dirty-paper theory. The method is presented with biorthogonal codes that have the best robustness. The advantage and trade-offs of using biorthogonal codes with this watermark coding methods are analysed comprehensively. The comparisons between orthogonal and non-orthogonal codes that are used in this watermarking method are also made. It is found that fidelity and robustness are contradictory and it is not possible to optimise them simultaneously. Comparisons are also made between all proposed methods. The comparisons are focused on three major performance criteria, fidelity, capacity and robustness. aom two different viewpoints, conclusions are not the same. For fidelity-centric viewpoint, the dirty-paper coding methods using biorthogonal codes has very strong advantage to preserve image fidelity and the advantage of capacity performance is also significant. However, from the power ratio point of view, the orthogonalisation methods demonstrate significant advantage on capacity and robustness. The conclusions are contradictory but together, they summarise the performance generated by different design considerations. The synchronisation of watermark is firstly provided by high contrast frames around the watermarked image. The edge detection filters are used to detect the high contrast borders of the captured image. By scanning the pixels from the border to the centre, the locations of detected edges are stored. The optimal linear regression algorithm is used to estimate the watermarked image frames. Estimation of the regression function provides rotation angle as the slope of the rotated frames. The scaling is corrected by re-sampling the upright image to the original size. A theoretically studied method that is able to synchronise captured image to sub-pixel level accuracy is also presented. By using invariant transforms and the "symmetric phase only matched filter" the captured image can be corrected accurately to original geometric size. The method uses repeating watermarks to form an array in the spatial domain of the watermarked image and the the array that the locations of its elements can reveal information of rotation, translation and scaling with two filtering processes

Handbook of Digital Face Manipulation and Detection

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area

Handbook of Digital Face Manipulation and Detection

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area