A single watermark based scheme for both protection and authentication of identities

IET Image ProcessingVolume 16, Issue 12 p. 3113-3132 ORIGINAL RESEARCHOpen Access A single watermark based scheme for both protection and authentication of identities S. Sharma, Corresponding Author S. Sharma [email protected] orcid.org/0000-0002-3185-6149 School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, Australia Correspondence S. Sharma, School of Engineering, Design and Built Environment, Western Sydney University, Locked Bag 1797, Penrith 2751, NSW, Australia. Email: [email protected]Search for more papers by this authorJ.J. Zou, J.J. Zou School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, AustraliaSearch for more papers by this authorG. Fang, G. Fang School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, AustraliaSearch for more papers by this author S. Sharma, Corresponding Author S. Sharma [email protected] orcid.org/0000-0002-3185-6149 School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, Australia Correspondence S. Sharma, School of Engineering, Design and Built Environment, Western Sydney University, Locked Bag 1797, Penrith 2751, NSW, Australia. Email: [email protected]Search for more papers by this authorJ.J. Zou, J.J. Zou School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, AustraliaSearch for more papers by this authorG. Fang, G. Fang School of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW, AustraliaSearch for more papers by this author First published: 03 June 2022 https://doi.org/10.1049/ipr2.12542Citations: 1AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract The security of a watermarking scheme is mainly categorised as either robust or fragile. The former can withstand an authorised alteration/attack, primarily used in copyright protection. The latter follows a zero tolerance towards any modification, used primarily in content authentication processes. The existing literature in the field projects that two separate watermarks are required to make a watermarking scheme robust and fragile, thus making the overall process cumbersome and complex. A novel image watermarking scheme that uses only one watermark while achieving both goals of copyright protection and authentication of identities is presented. An unconventional concept of checkpointing is introduced, which equips the proposed scheme to be either robust or fragile, making it superior in its application versatility. First, watermark embedding within the host/original image is achieved by a combination of transform domain techniques along with a novel median-based embedding block selection procedure. Second, checkpointing is performed in the spatial domain. The watermarked image in the absence of an attack is correlated to the one that is being attacked, using the template energy comparison-based approach. In the case of the robust watermark, such checkpointing can establish whether the carried out attack is authorised or not, determining the successful recovery of the watermark or vice-versa. Moreover, in the case of the fragile watermark, a sole confirmation of the occurrence of an attack is sufficient to make the watermark recovery impossible. Finally, the experimental analysis of the proposed scheme illustrates its excellent performance and superiority over state-of-the-art methods within the field. 1 INTRODUCTION In this era of technology, as more people and businesses are transitioning towards being digital, safeguarding their identity is the prime focus of any information security system. This being said, the year 2020 presented several unprecedented scenarios as COVID-19 has reshaped both the personal and the professional lives of people across the globe. It has altered the way businesses/organisations operate as the use of physical office space(s) has declined dramatically, forcing them to run from online. Consequently, internet usage has maximised, and many online platforms such as Zoom™, Webex™ are in the limelight. Furthermore, social networks (SNs) activity has hiked as more people tune in to these avenues. These mediums are beneficial as they have made it possible to stay connected in these isolating times; however, their other side is not that captivating as hacking and cyber-crimes have also skyrocketed. The affects of such adversaries are felt worldwide; for instance, in May 2020, Zoom faced an alarming trend known as "Zoom bombing", in which intruders hijacked the live video sessions and created nuisance [1]. Subsequently, in June, the information systems of services New South Wales (NSW), Australia, were infiltrated and numerous sensitive documents were stolen. Consequently, almost a quarter of a million Australians' ended up losing their personal information in the form of driver's licences, handwritten signatures, marriage and birth certificates [2]. Last but not least, the severity of such attacks is evident when performed on the SNs; for instance, the facebook™ security breach at the beginning of 2020 impacted its 50 million users. These users had their email accounts compromised, pictures/images stolen and the same goes for the twitter™ breach of July 2020 [3]. These are only a handful of snippets of the wide range of persisting cyber-attacks and thus, thwarting them is pivotal. Watermarking in this context is an effective and reliable tool, specifically for the platforms that use images/videos. The watermarking process includes an addition of subtle information known as the "watermark" to a host signal (an image in this paper). The added watermark can successively be extracted/recovered to verify the host image's authenticity and copyright information [4]. A successful extraction validates the integrity of the host image. A watermarking scheme needs to address three main requirements [5]. First, the addition of the watermark to a host signal has to be imperceptible. This avoids any deformities that may be perceived by the human visual system (HVS). Second, the watermark needs to be secured against unauthorised modifications. Lastly, a watermarking scheme should have a healthy capacity, that is, its ability to embed large watermark(s). However, these three requirements are closely correlated and changing one of these can significantly affect the other. For instance, high capacity can improve security but degrades imperceptibility. Whereas the lower the capacity, the better the imperceptibility, the weaker the security. Thus, reaching a balance among these requirements is a significant challenge in the field of watermarking. The security within watermarking is further sub-divided into two categories: robust and fragile [6]. The former can entertain a set of authorised modifications/attacks and is primarily used in copyright protection or similar applications. The latter is mainly used for authentication purposes as it simply opposes any modification. To achieve both goals of image authentication and copyright protection, two separate watermarks are being embedded in state-of-the-art methods. One is robust and the other fragile [7]. Notwithstanding the success of embedding multiple watermarks, the approach is prone to several limitations. First and foremost, as per the aforementioned discussion, embedding multiple watermarks can lead to a significant increase in capacity, thus, degrading the imperceptibility. Second, the addition of multiple watermarks is an uphill task, not preferred by the real-time applications. Finally, due to the increased capacity, the majority of these multipurpose techniques happen to be blind, thus, giving rise to security issues because in the blind watermarking technique, the original image is absent at the time of extraction. Such an absence makes it impossible to verify the extracted watermark against the original watermark. That is why the non-blind watermarking schemes are considered the most secured ones in the literature [5, 6, 8, 9]. To this end, this paper aims to present a non-blind watermarking scheme that uses only one watermark to achieve both goals of image authentication and copyright protection. A watermarking scheme can be robust or fragile, depending on the requirement of the practical application for which it is about to be employed. The proposed method uses a novel concept of checkpointing (discussed in Section 3.3) that makes the proposed scheme adapt to the requirement of either being robust or fragile. This concept highlights the versatility of the proposed method, and an insight into its application background can be gained from the following examples. First, many artists today use social network (SN) platforms to showcase their art. Unfortunately, these platforms are also the primary source of information leaks, and according to Bertini et al. [10], only one out of 13 main SNs uses watermarking technology Before uploading an image of their work on a SN, artists can embed the electronic version of their art with a robust watermark. This means, if an artist comes across a stolen version of their work, they can alert the relevant SN, and prove the copyright of their work via the robust watermark. Ultimately, they can have the stolen version of their work removed from the internet. Second, sensitive data, such as medical and military images, are not to be altered as it can result in severe consequences. To keep the authenticity of such images intact, they are embedded with a fragile watermark that can easily be broken even by the slightest change. Subsequently, the intactness of these images can be verified during the extraction process (discussed in Section 3.2). To this effect, if the watermark is successfully extracted, an image is considered legitimate else, it is illegitimate. The application versatility of the proposed method is further highlighted as the discussion in this paper progresses Our contributions The main contributions of the proposed scheme are listed below. 1. A novel median-based coefficient selection procedure in the frequency domain is proposed. This procedure is employed during the watermark embedding phase of this study (discussed in detail in the upcoming Section 3.1), wherein the carefully selected frequency coefficients are modified in equal proportions. To the best of the authors' knowledge, this is the first study wherein such a coefficient selection procedure is developed and employed. This procedure has two main benefits, as outlined below. It improves the watermark's imperceptibility. To this end, while operating on the greyscale images, the proposed watermarking is superior to existing state-of-the-art methods [5, 11-17] and also outperforms [18] and [19] while operating on the colour images. It improves the overall security attribute of the proposed scheme. The robustness of the watermark, embedded using the proposed novel median-based coefficient selection procedure, is tested against various geometrical and non-geometrical watermarking attacks (see [4] to gain an insight in the watermarking attacks). Its immunity is higher to such attacks than widely-cited methods [5, 11-20] in the field. Moreover, unlike most of the aforementioned existing watermarking techniques, the security evaluations of the proposed scheme are achieved using various watermarks of different dimensions, and the host images as small as 128 × 128 and as large as 2048 × 1152 in pixel resolution, respectively. 2. A novel concept that works in the spatial domain, which is termed by the authors as checkpointing, is introduced. The main benefit of this concept is that it empowers the proposed watermarking scheme to be adaptable to the requirement of being either robust or fragile. To the best of the authors' knowledge, checkpointing is the first of its kind concept that uses only one watermark to achieve both copyright protection and authentication goals. More details on checkpointing can be found in Section 3.3. The rest of this paper is organised as follows. Section 2 covers state-of-the-art literature in the field. Section 3 is dedicated to the proposed methodology. Section 4 covers the experimental results and finally, Section 5 is the conclusion. 2 RELATED WORK The term "Digital Watermarking" had its dawn in 1992 and since then it has been an active topic of research [21]. Its applications are continuously branching out to new advents in technology; for example, the process of watermarking a neural network is known as "passporting" [22, 23], security in cloud storage systems [24, 25], electronic money transfers, e-governance [26]. However, the use of watermarking for purposes of copyright protection and authentication has always been a key focus ever since its arrival [27, 28], thus is also the focus of this discussion. The state-of-the-art methods that have influenced the proposed scheme are discussed and summarised in this section and Table 1, respectively. TABLE 1. Summary and comparison of related works Method Watermark (s) Colour map Technique (s) Copyright protection Authentication Security Imperceptibility Capacity Sharma et al. [5] 1 Greyscale DWT ✓ $\checkmark$ × High High Medium Hurrah et al. [11] 2 Colour+Greyscale DWT+DCT ✓ $\checkmark$ ✓ $\checkmark$ High Medium High Kang et al. [12] 1 Greyscale DWT+DCT+SVD ✓ $\checkmark$ × High Low Low Verma et al. [13] 1 Greyscale DWT ✓ $\checkmark$ × HIgh Medium Low Islam et al. [14] 1 Greyscale DWT+SVM ✓ $\checkmark$ × High Medium Low Barr et al. [18] 2 Colour DWT ✓ $\checkmark$ × Lowest Lowest Lowest Loan et al. [15] 2 Colour+Greyscale DWT+DCT ✓ $\checkmark$ ✓ $\checkmark$ High Medium Highest Singh et al. [29] 2 Colour DWT+DCT+BPNN ✓ $\checkmark$ × Medium Low High Kamili et al. [19] 2 Colour DWT+DCT ✓ $\checkmark$ ✓ $\checkmark$ High Medium High Hurrah et al. [16] 1 Greyscale DWT ✓ $\checkmark$ ✓ $\checkmark$ High High High Kang et al. [17] 1 Greyscale DWT+DCT+SVD ✓ $\checkmark$ × High Medium Low Proposed 1 Colour+Greyscale DWT+DCT ✓ $\checkmark$ ✓ $\checkmark$ Highest Highest High A discrete wavelet transform (DWT) coefficient difference-based watermarking approach was developed by Lin et al. in [30]. Their technique is extensively used and embraced by many later works such as [13, 14]. Although their method successfully achieved very high imperceptibility with moderate capacity, it struggled from the security aspect [31]. The strategy of embedding multiple watermarks rectified this shortfall and is currently being used in identity (ID) protection or similar applications [18, 32, 33]. Lu and Liao pioneered the idea of multipurpose watermarking that achieved both authentication and copyright protection [34]. They successfully used DWT for embedding two separate watermarks to make their scheme both robust and fragile. Their method was only applicable to greyscale images and suffered from the tamper localisation issues, rectified by Liu et al. through a dual watermarking scheme on colour images [7]. They employed DWT in Y C b C r $YC_{b}C_{r}$ colour model, where Y, C b $C_{b}$ and C r $C_{r}$ are luminance, chrominance blue and chrominance red channels of a colour image, respectively. Subsequently, they used Y channel for robust watermark embedding in the transform domain and manipulated the least significant bits (LSB) for fragile watermark insertion in the spatial domain. Disadvantages associated with methods that are solely based on DWT are restricted if not nullified by pairing them with other techniques such as discrete cosine transform (DCT), singular value decomposition (SVD), support vector machine (SVM) and back propagation neural network (BPNN) [11, 12, 15, 20, 29, 35]. Moreover, these hybrid methods have their own flaws. For instance, BPNN or any other machine/learning-based technique initially requires intense computation power, data collection and training, making such methods expensive in terms of resource and processing time. Hence, integrating multiple processes into one is a cumbersome task. In addition to its fast processing ability and application simplicity, the main merit of DCT-based watermarking methods is their resilience to the image compression attack method, one of the most effective and widely used attacks [35, 36]. Hurrah et al. presented a dual watermarking framework for privacy protection and multimedia content authentication in [11]. Their method is employable across different colour spaces: greyscale and R G B $RGB$ (red-blue-green channels). Subsequently, they used DWT-DCT based embedding scheme along with Arnold transform-based encryption key. Their work motivated Kamili et al., who have recently proposed DWFCAT: a watermarking strategy for colour images. Unlike [11], DWFCAT employs Y C b C r $YC_{b}C_{r}$ colour-space. It exploits the energy compaction property of DCT coefficients for robust watermark embedding and fast processing is achieved by embedding fragile watermark bits in the spatial domain [19]. Their technique employs chaotic and deoxyribonucleic acid (DNA) encryption keys as a measure to ensure extra security. Although Kamili et al.'s method has high capacity, it under-performed in peak-signal-to-noise-ratio (PSNR) values. Subsequently, Hurrah et al. successfully proposed another dual watermarking strategy in [37], through which they were able to surpass the PSNR values attained by their preceding method in [11] and Kamili et al.'s method. The methods mentioned above motivate the proposed approach to use both DWT and DCT for the watermark embedding. Their combination leads to better imperceptibility and security; however, the proposed method is also outstanding in the following aspects. First, the majority of these aforementioned methods use at least two if not more encryption keys. This not only adds to the implementation complexity but also makes the whole process time-consuming. In contrast, the proposed method uses only one encryption key (discussed in detail in the upcoming section). Second, a dual watermarking technique can be tedious as it performs twice the watermark embedding and extraction procedures. The proposed method eradicates this issue as it uses only one watermark to achieve both copyright protection and media authentication goals. Finally, in addition to using both DWT and DCT, the proposed watermark embedding incorporates a novel median-based embedding block selection procedure. This block selection procedure is adaptive, thus, eliminates any errors that may occur in manual thresholding. The rest of the proposed methodology is covered in the following section. 3 METHODOLOGY An overview of the proposed method is given in Figure 1, in which the original image is divided into multiple frequency subbands through DWT. Note, the proposed scheme can be applied to both greyscale and colour images; for simplicity, discussion in this section is done by employing the greyscale colour-space. A separate subsection that presents the application on the colour images is dedicated to this paper's latter part. FIGURE 1Open in figure viewerPowerPoint Blueprint of the proposed method. The yellow arrows represent steps within the embedding phase and the green arrows are for the extraction process Precisely, the DWT of an image yields four frequency subbands, which are termed and represented in Figure 1 as L L $LL$ (Low-Low), L H $LH$ (Low-High), H L $HL$ (High-Low) and H H $HH$ (High-High). Commonly, the HVS is more receptive to low-frequency modulations. As the L L $LL$ subband is comprised of the low-frequency DWT coefficients, it is not suitable for the watermark embedding. Similarly, the H H $HH$ subband contains high-frequency coefficients, which can easily be victimised by the usual watermarking attacks, such as compression and high-pass filtering, leaving them unfit for embedding. Moreover, our previous works in [5, 9] are positively influenced by the literature in [13, 14, 30]. They tend to use the L H $LH$ (represented by solid blue in Figure 2) subband for the watermark embedding due to its ability to limit the flaws above, linked with L L $LL$ and H H $HH$ subbands. Furthermore, these methods also exploit the wavelet's ability to perform the multi-resolution analysis (MRA), through which an image can be decomposed into multiple levels to extract the DWT coefficients associated with these levels (see [38, 39] to gain an insight on the MRA). FIGURE 2Open in figure viewerPowerPoint The proposed watermark embedding process. Digits within Primary Blocks (PB-1 and PB-2) are the numbers allocated to DCT coefficients, where DC being the lowest frequency component is labelled as 1 and 64 is dedicated to the highest frequency component Notwithstanding the success of these methods in their application simplicity and faster processing, it is well-known that the MRA, specifically at levels higher than three, can lead to a number of issues, such as, aliasing which could be detrimental during the image reconstruction process and ultimately sacrifice the imperceptibility of the watermarked image. Further investigations by Thien et al. in [40-42] have highlighted that as the DWT level increases, the subband size decreases, and so is the watermark capacity. Therefore, it is recommended that utilising both L H $LH$ and H L $HL$ (represented by solid yellow in Figure 2) subbands is optimal in the embedding process. Additionally, it is suggested that as L H $LH$ and H L $HL$ are symmetrical in nature, therefore, while embedding a binary watermark, black (0) and white (1) bits can be evenly split amongst these two subbands. Consequently, it makes the watermark more resilient against several attacks such as the low-pass and high-pass filtering, rotation, scaling, translation while being high in capacity and imperceptibility. Convinced by these justifications, the proposed method uses both L H $LH$ and L H $LH$ subbands in the embedding process. Moreover, a thorough discussion on the watermark embedding in each of these subbands and their behaviour is covered by Islam et al. in [14]. Note, the default image dimensions/size accepted by 13 prominent SNs, recently studied by Bertini et al. in [10], are given in Table 2. This table shows that all of these SNs are defaulted to accept an image with dimensions in the power of two. Bertini et al. have also addressed that these SNs when presented with an image, consisting of an odd number of either rows or columns or both, perform a resizing operation that aligns the given image to its nearest power of two, thus, making it acceptable. The proposed method in this paper follows the same trajectory. Furthermore, such resizing is also essential to carry forward a DWT operation as it yields frequency subbands that are even in size. Subsequent steps shown in Figure 1 are discussed in the upcoming subsections, covering the proposed watermark embedding and extraction, respectively. TABLE 2. Default image sizes accepted by SNs Index SN Pixel resolution 1 Facebook 2048 × 1152 2 Flickr 2048 × 1152 3 Google+ 2048 × 1152 4 Instagram 1080 × 1080 5 LinkedIn 2048 × 1152 6 Pinterest 2048 × 1152 7 Telegram 1280 × 720 8 Tumblr 1280 × 720 9 Twitter 2048 × 1152 10 Viber 1280 × 720 11 VK 2560 × 1440 12 WeChat 1280 × 720 13 WhatsApp 1600 × 1200 Watermark embedding A breakdown of the proposed embedding strategy is provided in Figure 2. First, the host image of size m× n (rows× columns) is decomposed into frequency subbands using DWT. The proposed method is fully able to handle images with pixel resolutions mentioned in Table 2; however, for the sake of explanation simplicity, the rest of the proposed method is elaborated by considering a host image of dimensions 512× 512 in pixels. Second, LH and HL subbands, composed of the DWT coefficients and each having 256× 256 pixels in size, are divided into 8× 8 non-overlapping blocks. Subsequently, the DCT is performed on each of these 8× 8 blocks to yield their respective DCT coefficients and collectively, they form a primary block that is termed "Primary Block" in Figure 2. Moreover, the primary block associated with the H L $HL$ subbands is labelled as "Primary Block-1" (PB-1), whereas the one related to the L H $LH$ block is labelled as "Primary Block-2" (PB-2). A magnified illustration of these primary blocks is presented in Figure 2. The digits within these blocks depict the position numbers associated with the DCT coefficients, of which these blocks are constructed. Based on their frequency, DCT coefficients are classified as low-frequency (LF), mid-frequency (MF) and high-frequency (HF) and the very first low-frequency coefficient is known as the direct-current (DC) coefficient, respectively (see Figure 2). In this paper, MF coefficients are selected for the watermark embedding as these coefficients, unlike their counterparts (LF and HF coefficients), allow alterations while maintaining a harmonious balance between imperceptibility and robustness. Furthermore, a full account on the behaviour of DCT coefficients can be found in [36]. Similar to [12], a "Secondary Block" (SB), is constructed by eight of the total MF coefficients in a primary block; their allocated position numbers in Figure 2 are 13, 16 − 21, 25. The secondary block contained within PB-1 is termed as SB-1 and the one within PB-2 is labelled as SB-2. Third, the individual median values of PB-1 and PB-2 are calculated and successively, tagged as P B 1 m e d i a n $PB1_{median}$ (Primary Block-1 Median) and P B 2 m e d i a n $PB2_{median}$ (Primary Block-2 Median) and so are the medians of secondary blocks with S B 1 m e d i a n $SB1_{median}$ (Secondary Block-1 Median) and S B 2 m e d i a n $SB2_{median}$ (Secondary Block-2 Median). Thereafter, the difference between P B 1 m e d i a n $PB1_{median}$ and S B 1 m e d i a n $SB1_{median}$ is calculated and depicted as Δ1. Similarly, the difference between P B 2 m e d i a n $PB2_{median}$ and S B 2 m e d i a n $SB2_{median}$ is docketed as Δ2. Figure 3 provides the pictorial representation of median calculations and literature in [15] and [43] provides further insight on these median estimations. FIGURE 3Open in figure viewerPowerPoint Median value calculations Subsequently, the watermark (W1) is prepared by a series of steps, as shown in Figure 2. The first step is thresholding the watermark to a pixel value of 128. It yields its binary equivalent and limits it to 0 (Black) and 255 (White) in values, referred to as 0 and 1 in binary. Second, the secret key is used to scramble the binary watermark. Such a secret key is vital during the transmission of the watermarked image because this very key is employed at the time of its validation, achieved via watermark extraction (discussed later in this paper). Due to its robust performance and state-of-the-art usage, the Fisher-Yates shuffle algorithm is employed in this paper to achieve watermark scrambling (see [13, 44, 45] to gain further insight on this shuffling algorithm). Once the watermark is prepared and values of Δ1 and Δ2 are calculated, the maximum ( S B 1 C m a x $SB1C_{max}$ ) and second-maximum ( S B 1 C m a x 2 $SB1C_{max2}$ ) valued coefficients within a secondary block, SB-1 are modified to meet the following criterion. If the watermark bit to be embedded ( W e m $W_{em}$ ) in the SB-1 is 1, then, S B 1 C m a x = S B 1 C m a x n e w = Δ 1 ξ 1 S B 1 C m a x 2 = S B 1 C m a x 2 n e w = Δ 1 / ξ 1 , \begin{align} \begin{split} {SB1C_{max}}={SB1C^{new}_{max}}=\Delta _{1}\xi _{1}\\ {SB1C_{max2}}={SB1C^{new}_{max2}}=\Delta _{1}/\xi _{1} \end{split}, \end{align} (1)and if it is 0, then, S B 1 C m a x = S B 1 C m a x n e w = Δ 1 / ξ 1 S B 1 C m a x 2 = S B 1 C m a x 2 n e w = Δ 1 ξ 1 , \begin{align} \begin{split} {SB1C_{max}}={SB1C^{new}_{max}}=\Delta _{1}/\xi _{1}\\ {SB1C_{max2}}={SB1C^{new}_{max2}}=\Delta _{1}\xi _{1} \end{split}, \end{align} (2)where ξ1 stands for the average median value of selected SB-1 blocks from the total SB-1 blocks. ξ1 is calculated as per Equation 3 in which ⌊ . ⌋ $\lfloor {.}\rfloor$ or anywhere else in this paper stands for the floor function. Similarly, M b $M_{b}$ stands for the aforementioned selected SB-1 blocks, selected as per Figure 4. ξ 1 = ∑ i = 1 M b S B 1 m e d i a n i M b . \begin{align} \xi _{1} = \left\lfloor {\frac{\sum ^{M_b}_{i=1}SB1^{i}_{median}}{M_b}}\right\rfloor . \end{align} (3) FIGURE 4Open in figure viewerPowerPoint Block selection procedure. The selected SB-1 blocks are between the green labels Likewise, in the case of embedding in the secondary block, SB-2, Equations (1) and (2) can be rewritten as Equations (4) and (5), respectively. If the watermark bit to be embedded ( W e m $W_{em}$ ) in the SB-2 is 1, then, S B 2 C m a x = S B 2 C m a x n e w = Δ 2 ξ 2 S B 2