The protection of copyrights of digital media uploaded to the Internet is a growing problem. In this paper, first, we present a unified framework for embedding and detecting watermark in digital data. Second, a new robust watermarking scheme is proposed considering this concern. The proposed work incorporates three chaotic maps which specify the location for embedding the watermark. Third, a new chaotic map, the Extended Logistic map, is proposed in this work. The proposed map has a bigger range than logistic and cubic maps. It has shown good results in a bifurcation, sensitivity to initial conditions, and randomness tests. Furthermore, with the detailed analysis of initial parameters, it is justified that Extended Logistic map can be used in secure communication, particularly watermarking. Fourth, to check the robustness of proposed watermarking scheme, we have done a series of analyses and standard attacks. The results confirm that the proposed watermarking scheme is robust against visual and statistical analysis and can resist the standard attacks.
With the exponential growth of multimedia and their applications, most of the digital data is exchanged thorough the insecure channel [
At the time of claiming the copyrights, inverse watermarking function
This kind of watermarking scheme is known as private watermarking in which only
This sort of watermarking scheme is known as public watermarking. In this manuscript, we have employed the private watermarking scheme using three chaotic maps which serve the functionality of
Although there have been tremendous works on watermarking for the copyrights protection still the practical and real-life applications do need much attention, specifically in the area of online privacy of digital data. For example, a public domain of video uploader, youtube.com, does not have the sophisticated framework for the protection of rightful ownership. Let say, for instance, Bob has uploaded his video and after some time (days), Alice has downloaded that video and uploaded it again by her name. At the time of uploading, Alice has been granted the permission of uploading that video which should not be the case. The management of that public domain eventually remove that video after some days, and if the name of the video uploaded by Alice is significantly different from the one given by Bob, then it can take even more time to look up for that video and eventually in removing the video. Similarly, other than videos, piracy of digital images face the same problem.
In this work, we have proposed a unified framework for protecting the rightful ownership of digital data. The proposed framework is shown in Figure
A top level block description of the proposed unified framework for protecting the rightful ownership of digital data. If an unauthenticated user tries to download and upload a data of user
In this paper, we develop a framework for watermarking using three different chaotic maps. The proposed work is effective and efficient as evident from the different analysis and attacks examined. The contributions of this paper are summarized as follows: We have proposed a unified framework for the protection of rightful ownership. In this framework, the wrong owner is not only denied but also reported to the right owner for any legal case. We have proposed a new chaotic map, Extended Logistic map in this work. The proposed map has a bigger range than logistic and cubic maps. It has shown good results in a bifurcation, sensitivity to initial conditions, and randomness tests. Furthermore, with the detailed analysis of initial parameters, it is justified that Extended Logistic map can be used in secure communication, particularly watermarking. We have proposed a watermarking scheme for any digital data specifically image data. The proposed watermarking is primarily based on the embedding of a watermark in lease significant bits of the carrier using three different chaotic maps. The initial conditions of these three chaotic maps are considered as secret keys [ We have done noise resistant analysis in which we have shown that if the watermarked image is corrupted by the channel noise or by an unauthorized user, the inverse watermarking algorithm can correctly extract the watermark from the corrupted watermarked image with some minor changes. To evaluate the strength of proposed watermarking algorithm, we have done a series of analyses along with standard attacks. The results of these analyses showed the superior performance and robustness of our proposed watermarking algorithm.
The remaining part of the manuscript is planned as follows: Section
This section will briefly introduce a new chaotic map which is a combination of logistic and cubic chaotic maps. The importance of usage of the proposed chaotic map is illustrated through the bifurcation diagrams, randomness, and sensitivity tests. The basics of other chaotic maps employed in the proposed watermarking algorithm are also given. These maps are piecewise linear chaotic map and Tangent Delay Ellipse Reflecting Cavity Map System (TD-ERCS).
The logistic chaotic map is given as [
The cubic chaotic map is given as [
Combining the above two maps, the new proposed Extended Logistic (EL) chaotic map is given as
We have analyzed the bifurcation diagrams of the EL map considering different values of parameter
Bifurcation diagrams of the EL map considering different values of parameter
In addition, we have examined a bifurcation diagram shown in Figure When When When
(a) Bifurcation diagram of EL map for
(a) Bifurcation diagram of EL map for
(a) Bifurcation diagram of EL map for
The chaotic behavior is further tested using the standard NIST-800-22 statistical tests [
NIST statistical tests to check the randomness of chaotic sequences generated by EL map for initial conditions of
Statistical Test | | Decision |
---|---|---|
Frequency (Mono Bit) Test | 0.9984 | Passed |
Frequency Test within a Block | ||
(Blocks sizes: 3, 4, 5, 6, 7, 8) | 0.6845 | Passed |
The Runs Test | 0.0409 | Passed |
Tests for the Longest-Run-of-Ones in a Block | ||
(Blocks size: 8) | 0.3089 | Passed |
The Binary Matrix Rank Test | ||
(4 Matrices, Rows: 8, Columns: 8) | 0.0886 | Passed |
(16 Matrices, Rows: 4, Columns: 4) | 0.1547 | Passed |
The Discrete Fourier Transform (Spectral) Test | 0.1007 | Passed |
The Non-overlapping Template Matching Test | ||
(Template length = 4, Blocks = 2, 4, 8) | 0.0314 | Passed |
The Overlapping Template Matching Test | ||
(Template length = 4, Blocks = 4, 8) | 0.5947 | Passed |
Maurer’s Universal Statistical Test | 0.2514 | Passed |
The Approximate Entropy Test | 0.3108 | Passed |
The Cumulative Sums (CUSUM) Test | 0.4512 | Passed |
For the appropriate usage in secure communication, randomness alone is not enough for a chaotic map. One of the essential requirements for any random generator in security is to be sensitive to the initial conditions. We have plotted chaotic sequence for EL map for initial conditions of
(a) Chaotic sequence for EL map for initial conditions of
It can be shown that the other two chaotic maps, TD-ERCS and piecewise linear map, also have the same properties as EL map. The TD-ERCS map gives two chaotic sequences,
And the initial seed parameters are
Given these initial parameters, we have
The third chaotic map that will be employed is piecewise linear chaotic map, given as [
The proposed work is intended for the online multimedia copyright protection. The watermark is inserted into a carrier based on the decisions made by three chaotic maps. The watermark which we want to insert is taken as a byte of length with eight binary bits, even if it is a digital signal, sound data, image data, video data, or simply text. Beside the watermark insertion, a substitution operation is also performed on watermark to enhance the security of the overall system. The watermarking and inverse watermarking processes are explained as follows.
The watermarking algorithm in the form of a flowchart is shown in Figure
Before the watermark insertion, the watermark is divided into eight binary bits in which 4 Least Significant Bits (LSBs) of each pixel are discarded, keeping the 4 Most Significant Bits (MSBs). The reason for reducing the size of watermark image is to decrease the computational complexity while keeping the texture of watermark image as same as possible; this is shown in the simulated results carried later. The 4 MSBs are substituted with the 4
For simplicity and convenience, we write substituted watermark image as
Presentation of S-Box in 4
R/C | 0 | 1 | 2 | 3 |
---|---|---|---|---|
0 | 11 | 1 | 7 | 13 |
1 | 5 | 15 | 4 | 2 |
2 | 6 | 12 | 9 | 14 |
3 | 10 | 0 | 3 | 8 |
Graphical illustration of 4
Flowchart of the watermarking algorithm is comprised of three chaotic maps with the help of a 4
Let
Let
Let
In parallel, the
EL map, and secret keys:
The inverse watermarking algorithm which is exactly the inverse of the watermarking algorithm in the form of a flowchart is shown in Figure
Flowchart of the inverse watermarking algorithm is comprised of three chaotic maps with the help of a 4
As a first step of the inverse watermarking algorithm, the chaotic sequences are generated from three chaotic maps using the same set of secret keys. In parallel, for the extraction of watermark, the
keys:
The simulations are conducted taking the first baboon as carrier image with size 512
Values of secret keys which are the initial conditions of the three chaotic maps employed in the proposed watermarking algorithm.
Maps | Parameters | ||||||
---|---|---|---|---|---|---|---|
| | | | | | | |
EL Map | 0.5 | - | - | - | 1.46 | - | 2 |
TD-ERCS Map | 0.5 | 1 | 0.4 | 50 | - | - | - |
Piece Wise Map | 0.4 | - | - | - | 3.7 | 0.9 | - |
(a) Watermark cameraman image; (b) watermark cameraman image after discarding 4 Least Significant Bits (LSBs) of each pixel. It can be seen that there is not much difference of texture between these two images (a and b). (c) Substituted version of watermark by substituting the after-discarded version of watermark with the S-Box shown in Table
(a) The baboon image which is considered as a carrier. (b) The watermark which is to be inserted. (c) After insertion, the watermarked baboon image. We can see that these two images, carrier and watermarked, are visually similar to each other. After the extraction of watermark from the watermarked image, we expect to get the cameraman image shown in (b). (d) Histogram of the carrier image and (e) histogram of the watermarked image.
To examine the visual strength of the proposed watermarking algorithm, different statistical analyses are performed on carrier and watermark to compare the visual appearance of these two images. The statistical analysis considered in this work is as follows.
The correlation of an image is given as [
The entropy of an image is given as [
The contrast of an image is given as [
The homogeneity of an image is given as [
The energy of an image is given as [
The results of these analyses considering our proposed algorithm for the carrier and watermarked images are shown in Table
Comparative statistical analysis on the carrier and watermarked images. The analyses are done on the individual three frames of these two images. It can be seen that, except the entropy analysis, the values of all the other analysis are same for all three frames of these two images showing very good performance.
Frame No. | Images | Analysis | ||||
---|---|---|---|---|---|---|
Corr. | Entropy | Homo. | Contrast | Energy | ||
1 | Carrier | 0.9570 | 7.6605 | 0.8872 | 0.2369 | 0.1062 |
Watermark | 0.9570 | 7.6602 | 0.8872 | 0.2369 | 0.1062 | |
| ||||||
2 | Carrier | 0.9330 | 7.3575 | 0.8844 | 0.2434 | 0.1244 |
Watermark | 0.9330 | 7.3569 | 0.8844 | 0.2434 | 0.1244 | |
| ||||||
3 | Carrier | 0.9610 | 7.6779 | 0.8806 | 0.2518 | 0.1040 |
Watermark | 0.9610 | 7.6772 | 0.8806 | 0.2518 | 0.1040 |
Table
A comparison of statistical analysis of other watermarking techniques [
Images | Other Works | Analysis | ||||
---|---|---|---|---|---|---|
Homo. | Contrast | Energy. | Entropy | Corr. | ||
Pepper | Original | 0.8902 | 0.3311 | 0.1330 | 7.5612 | 0.9207 |
Watermarked [ | 0.8917 | 0.3181 | 0.1233 | 7.6003 | 0.9295 | |
Watermarked [ | 0.8902 | 0.3311 | 0.1330 | 7.5613 | 0.9207 | |
Watermarked [ | 0.8512 | 0.3241 | 0.1520 | 7.4521 | 0.6241 | |
Watermarked, Proposed | 0.8902 | 0.3311 | 0.1330 | 7.5641 | 0.9207 | |
| ||||||
Lena | Original | 0.8651 | 0.4141 | 0.0942 | 7.7021 | 0.9444 |
Watermarked [ | 0.8687 | 0.3857 | 0.1288 | 7.2512 | 0.8933 | |
Watermarked [ | 0.8811 | 0.3371 | 0.1130 | 7.7023 | 0.9443 | |
Watermarked [ | 0.9277 | 0.2688 | 0.3208 | 7.6745 | 0.9688 | |
Watermarked, Proposed | 0.8651 | 0.4141 | 0.0942 | 7.7045 | 0.9444 | |
| ||||||
Baboon | Original | 0.7294 | 1.0004 | 0.0817 | 7.3903 | 0.6607 |
Watermarked [ | 0.8427 | 0.3531 | 0.1387 | 7.1872 | 0.8933 | |
Watermarked [ | 0.7294 | 1.0004 | 0.0817 | 7.3903 | 0.6607 | |
Watermarked [ | 0.7669 | 0.7179 | 0.1028 | 7.4521 | 0.6788 | |
Watermarked, Proposed | 0.7294 | 1.0004 | 0.0817 | 7.3945 | 0.6607 |
The security analysis assists in determining the strength of any security algorithm. In this section, we have done detailed security analysis which includes key security, noise resistant analysis, and different attacks. These security analyses are described as follows.
Key space refers to the total number of keys that can be used in the watermarking algorithm. We have used initial conditions of three chaotic maps as the secret keys. There are nine secret keys used; the values of these secret keys with their ranges are mentioned earlier. If the average range of a secret key is
The key space will only be effective if every key is effective regarding successful extraction of the watermark. For example, key space will only be effective if we tried to extract the watermark from the watermarked image with a slightly change (even change of a single bit) secret key(s) that was used in the embedding of a watermark in carrier image, then the extraction should not be successful. This is known as key sensitivity. In this work, we have embedded the cameraman image with the secret keys mentioned in Table
Four different cases of key sensitivity. (a) Key used in extraction of watermark is changed from
One of the necessary features of a modern security system is to be noise resistant [
Noise addition results on watermarked images. (a) The watermarked image in which pixels from different locations are corrupted or cropped with the white pixels. (b) The watermarked image in which salt and pepper noise with density equal to 0.05 is added. (c) The watermarked image in which salt and pepper noise with density equal to 0.1 is added to further test the robustness.
The watermark images after extracting the watermark form the noisy watermarked images. (a) The watermark extracted from Figure
The robustness to noise attacks can be numerically measured as well through the confidence measure proposed by [
We have performed this confidence measure on our proposed technique as comparison to other works as well. However, for comparison, we have taken the value of similarity as a percentage instead of exact value. Table
A comparison results of similarity of different watermarking techniques resulting in applying various noise attacks. Again, it can be seen that the proposed work has superior performance.
Attacks | Other Works | Images/Similarity Index (%) | ||
---|---|---|---|---|
Baboon | Lena | Pepper | ||
Noise | Ref. [ | 72 | 74 | 73 |
Ref. [ | 72 | 74 | 73 | |
Proposed | 88 | 89 | 88 | |
| ||||
Compression | Ref. [ | 67 | 69 | 69 |
Ref. [ | 67 | 69 | 70 | |
Proposed | 85 | 81 | 84 | |
| ||||
Cropping | Ref. [ | 40 | 42 | 39 |
Ref. [ | 40 | 42 | 39 | |
Proposed | 68 | 69 | 67 |
In this attack, the attacker attempts to find the visual difference between the LSBs of carrier image and watermarked image. As the watermark is embedded into the LSBs of carrier image, this attack has the significance importance. It is assumed that the attacker has access to the watermarked image and carrier image as well (although this assumption leads to the compromise of the carrier and correspondingly the copyrights of this carrier image). The attacker plots the LSBs of the carrier and watermarked images and then tries to find the differences and subsequently tries to extract the watermark. It is required in a good watermarking algorithm that no visual difference should be visible. For the plot, we have picked the 4 LSBs of the carrier and watermarked images and consider them as 4 MSBs of these two images, and for 4 LSBs, we simply consider four zeros. Figure
(a) LSBs of carrier image before the embedding of watermark and (b) LSBs of watermarked image after the embedding of watermark. For the plot, the 4 LSBs of carrier and watermarked images are picked and consider them as 4 MSBs of these two images and for 4 LSBs, 4 zeros are simply considered. It can be seen that there is no visual difference between these two images and thus our proposed algorithm is robust against LSB attack.
One of the other methods to analyze the LSBs in a watermarked image is to see the difference between adjacent pixels. In an image, the correlation between two adjacent pixels is very high, and thus the difference between these two image pixels is usually close to zero. However, when the watermark is embedded into the LSBs of carrier image to generate a watermarked image, the correlation between adjacent pixels decreases where the watermark is embedded, and the difference of these two image pixels moves away from zero. It is required that the difference between adjacent pixels of both the carrier and watermarked images should be same to each other or near to each other. We have plotted the difference between adjacent pixels of the carrier and watermarked images to see the similarity between these two images. Particularly, we have plotted the difference of adjacent pixels of individual frames of all three frames of the carrier and watermarked images. Figures
(a)-(c) The difference of adjacent pixels for frames 1-3 of carrier and watermarked images when the difference is considered row-wise. In row-wise, the difference of those two image pixels is considered whose positions are in same row but separated by a single column. Similarly, (d)-(f) show the difference of adjacent pixels for frames 1-3 of carrier and watermarked images when the difference is considered column-wise. In column-wise, the difference of those two image pixels is considered whose positions are in same column but separated by a single row. In all these images, the differences of adjacent pixels of carrier and watermarked images are almost the same showing the robustness of proposed watermarking algorithm.
It is assumed for a long time since the sophistication of watermarking techniques that the LSBs of a digital image do not contain the important information regarding the image. However, this is not the case for all the images. There are works in the literature on watermarking attacks that suggest examining the LSBs of the carrier and watermarked images to possibly extract the watermark from the watermarked image. To further elaborate this point, we have plotted the single bits of carrier image of a baboon to examine the important information. Figure
(a) The plot of 7th LSB (‘xBxxxxxx’, B is the 7th bit) of carrier image; the information is clearly visible due to high percentage of information (50%) present in it. However as we move towards the next LSBs, the information tends to lose as can be seen in (b) and (c) which show the plot of 6th and 5th LSB, respectively.
(a) The plot of second LSB and (b) the plot of first LSB of carrier image of baboon. As the watermark is embedded in these 2 LSBs of carrier image to get the watermarked image therefore it is necessary that the plot of individual bits of first and second LSBs of watermarked image should be similar to the plots of bits of carrier image. (c) The plot of second LSB and (d) the plot of first LSB of watermarked image. It can be seen that these two plots are very similar to the plots of carrier image and they do not give any information about the watermark, thus showing the robustness of proposed watermarking algorithm.
We have developed a unified watermarking algorithm using three different and distinct chaotic maps in which one map is proposed in this work. The embedding of the watermark is operated by the individual chaotic sequence generated by a different chaotic map. The simulation results and security analysis confirmed that the proposed algorithm is secure against well-known attacks. Like all new proposals, we strongly encourage the analysis of our framework before its immediate deployment. The proposed algorithm is a generalized watermarking model that can incorporate changes as required. For instance, the number of substitution boxes can be increased for better security but at the expense of more computational complexity. Furthermore, the work can be extended for the application of steganography as well in which instead of the watermark, the secret message can be inserted for information hiding.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under Grant no. R.G.P-1/5/38.