Digital Watermarking

If one image can equal to thousand words then there is no reason for less growth of images for communication. Growing volume of images and use of image analytics for forecasting of market is tremendous. Apart from billions of camera exists, there are billions of mobile phones are being used in the Indian market and majority of them are equipped with camera. If every camera clicks only one image per day then what is the volume of images and what amount of space required to save these images is not tough to imagine. Digital watermarking is not new for the market but watermarking for the compressed encrypted images is relatively new and appealing. To save space, a large volume of data is being kept in the compressed encrypted format. For the various reasons, there is a great issue of copyright protection for these images. Growth of compressed encrypted image has magnified the need for more advanced watermarking techniques. In this paper we are trying to deal with the issues of copyright in the compressed encrypted images and review related work done by scientific community on various methods. We also are trying to address new future challenges of digital watermarking in the area of compressed encrypted image.
Keywords: Digital image, digital watermarking, encryption, compression, copyright.

I. Introduction:
In 440 BC, Histiaeus shaved a head of his most trusted slave and tattooed it with a massage which disappeared after hair had re-grow. To instigate revolt against Persians. In 1st and 2nd world war German spies invisible ink to print very small dots on the letters. And now special inks are used to write hidden messages on bank notes. Global piracy costs music recording industry over ?? 3.5 bn a year and still growing. History is full of news about piracy and information stealing. As time passes, many thinkers and researchers proposed different information hiding techniques to claim authenticity and deals with ownership of the information. Digital data is increasing manifold and continuously it changes its format. Images are the most valuable tool to communicate. Social media is full of images. Data and information flooded in the cloud are creating new debate about ownership issues. Indian politics are surrounding about images and information available on the social media account of the parties and politicians. Sometime information is false and many times these are used to claim false to gain political mileage. Similarly in the efficient stock market, market reacts on each and every news flow from any means and corner. Data flow from market to individual investor is needed to authenticate in such way that information reached to the investors have great credentials. Evolution of high performance computing (HPC) and related technologies are demanding to deal with very large volume of data. That is unstructured and Big. To deal with the unstructured data, a new means of watermarking is required which is applicable to the structured as well as unstructured data set. Irrespective of the data format, watermarking algorithm must be robust enough. Digital images and information in big data integration are always in question. Not only in social media but other walks of life also deals with the similar problems. Ownership of the information must be define and design in such way that it can't be published without ownership definition. Techniques like watermarking played a great role in the ownership definition and authentication of data. Some of the emerging areas are

a) Compressed encrypted data watermarking applicable for JPEG2000 format.
b) Big data applications in the field of medical science, stock market, social media, cloud computing etc are the best niche area for new watermarking technique.
World of computing is greatly concern with green technologies and methodologies. Efficiently dealing with the watermarking in the big data is big issue. This paper tries to review all related watermarking techniques applied in world of computing and reveals new areas where watermarking can play much bigger role for human kind as whole and information science as particular.
Digital watermarking is an efficient technique for copyright protection for text, image, audio, and video data. History is full of literature on digital watermarking. But watermarking in compressed and encrypted data requires new school of thought. Scientific community had been suggested ample number of technologies to hide information for the protection of copyright and related issues in compressed encrypted data. Watermarks allow embedded signals to be extracted from audio and video content for a variety of purposes. One application is for copyright control, where it is envisaged that digital video recorders will not permit the recording of content that is watermarked as 'never copy.' In such a scenario, it is important that the watermark survive both normal signal transformations and attempts to remove the watermark so that an illegal copy can be made. In the early years of 1998 ' 99, watermark techniques are used for resistant to tampering and describe a variety of possible attacks [10]. Then after an additive watermarking technique for grey-scale pictures is being came into existence. It consists in secretly embedding copyright information (a binary code) into the picture without degrading its quality. Those bits are encoded through the phase of maximal length sequences (MLS). MLS are binary sequences with good correlation properties. The result of the autocorrelation is much greater than cross correlations, i.e. correlations made with shifted versions of this sequence. The embedded bits are retrieved from the result of the correlations. The core of the embedding process is under laid by a masking criterion that guarantees the invisibility of the watermark. It is combined with an edge and texture discrimination to determine the embedding level of the MLS, whose bits are actually spread over 32*8 pixel blocks [11]. Then after digital audio, video, and pictures are increasingly furnished with distinguishing but imperceptible marks, which may contain a hidden copyright notice or serial number or even help to prevent unauthorized copying directly. Military communications systems make increasing use of traffic security techniques which, rather than merely concealing the content of a message using encryption, seek to conceal its sender, its receiver or its very existence. Similar techniques are used in some mobile phone systems and schemes proposed for digital elections. Criminals try to use whatever traffic security properties are provided intentionally or otherwise in the available communications systems, and police forces try to restrict their use. However, many of the techniques proposed in this young and rapidly evolving field can trace their history back to antiquity; and many of them are surprisingly easy to circumvent [7]. By year 2003 onwards wavelets and related methodologies were used for hiding text. The watermark is embedded in the significant wavelet coefficients by a simple exclusive OR operation. The method avoids complicated computations and high computer memory requirements that are the main drawbacks of common frequency domain based watermarking algorithms. Simulation results of these methods were show that the embedded watermark is perceptually invisible and robust to various operations, such as low quality joint picture expert group (JPEG) compression, random and Gaussian noises, and smoothing (mean filtering) [4]. In particular, authenticity is verified before full reconstruction of the original image, whose integrity is inferred from the reversibility of the watermarking procedure. This reduces computational requirements in situations when either the verification step fails or the zero-distortion reconstruction is not required. A particular instantiation of the framework is implemented using a hierarchical authentication scheme and the lossless generalized-LSB data embedding mechanism [13]. Then after, a new method called novel high capacity data hiding method based on JPEG was proposed. This method employs a capacity table to estimate the number of bits that can be hidden in each DCT component so that significant distortions in the stego-image can be avoided. The capacity table is derived from the JPEG default quantization table and the Human Visual System (HVS). Then, the adaptive least-significant bit (LSB) substitution technique is employed to process each quantized DCT coefficient. The proposed data hiding method enables us to control the level of embedding capacity by using a capacity factor [09]. Novel architecture for joint fingerprinting and decryption that holds promise for a better compromise between practicality and security for emerging digital rights management applications is very impressive [6]. Medical images are becoming more challenging for the human based technologies. For this a new technique is then adapted here for interleaving patient information and message authentication code with medical images in a reversible manner, that is using lossless compression. The resulting scheme enables on a side the exact recovery of the original image that can be unambiguously authenticated, and on the other side, the patient information to be saved or transmitted in a confidential way. To ensure greater security the patient information is encrypted before being embedded into images [16]. Till now, digital watermarking is based on system algorithms and users haven't any role in generating keys. A new user based watermarking was introduced and User-key-dependent removable visible watermarking system (RVWS) was come into existence. The user key structure decides both the embedded subset of watermark and the host information adopted for adaptive embedding. The neighbor-dependent embedder adjusts the marking strength to host feature and makes unauthorized removal very difficult. With correct user keys, watermark removal can be accomplished in 'informed detection' and the high quality unmarked image can be restored. In contrast, unauthorized operation either overly or insufficiently removes the watermark due to wrong estimation of embedding parameters, and thus, the resulting image has apparent defect [20]. Use of Mojette transformation is relatively new in hiding information. In this proposed technique advantage of the Mojette transform properties was coined, and can easily be included in distributed storage architecture. The basic crypto-compression scheme presented is based on a cascade of Radom projection which enables fast encryption of a large amount of digital data. Standard encryption techniques, such as AES, DES, 3DES, or IDEA can be applied to encrypt very small percentages of high resolution images [1]. Data from medical sciences needs special care. Authentication requires at highest degree. To reach villages at remote areas of the third world countries a new technology based medical science is evolve that is called telemedicine. Securing telemedicine by looking at attacks to the security by viewing the function of the computer system as provision of information is introduced. Watermarking is introduced as one of the security tool, using the medical image as the channel for watermarking. The main objectives for medical image watermarking are that the watermarks are imperceptible and act as a mean of authentication and integrity control. The issues in watermarking medical images raised here are complete authentication Vs content authentication, reversible watermarking Vs permanent/irreversible watermarking and the practical issue of compression [12]. So far, few solutions have been proposed to combine image encryption and compression for example. Nowadays, a new challenge consists to embed data in encrypted images. Since the entropy of encrypted image is maximal, the embedding step, considered like noise, is not possible by using standard data hiding algorithms. A new idea is to apply reversible data hiding algorithms on encrypted images by wishing to remove the embedded data before the image decryption. Recent reversible data hiding methods have been proposed with high capacity, but these methods are not applicable on encrypted images [19]. MPEG2 video encryption and watermarking is the best example. In this example, the DCs in intra macro blocks are encrypted or watermarked based on random module addition, while the DCs in other macro blocks and all the ACs' signs are encrypted with a stream cipher or block cipher. Analysis and experiments show that the scheme obtains high perceptual security and time efficiency, and the watermarking and encryption operations can be commutated. These properties make the scheme a suitable choice for efficient media content distribution [17]. A novel method for watermarking and ciphering color images, based on the joint use of a key-dependent wavelet transform with a secure cryptographic scheme is presented. The system allows to watermark encrypted data without requiring the knowledge of the original data and also to cipher watermarked data without damaging the embedded signal. Since different areas of the proposed transform domain are used for encryption and watermarking, the extraction of the hidden information can be performed without deciphering the cover data and it is also possible to decipher watermarked data without removing the watermark [8]. The VQ-based data hiding technique has not received much attention compared to various spatial domain based data hiding techniques in digital images. Consequently, a new data hiding scheme, applied in the VQ compressed domain of cover images, is introduced in this article. To provide more hiding capacity for secret data and to keep an acceptable bit rate for the compressed cover images, the search-order-coding (SOC) algorithm was implemented to compress the VQ indices of the cover images in the process of data hiding. During the process of data hiding, the proposed scheme embeds secret data into the compressed VQ indices of the cover image adaptively, adjusting the bit rate according to the size of the secret data and the compressed cover image. In addition, the hiding process induces no extra coding distortion [18]. After 2008, a public video watermarking algorithm, whose robustness depends on the embedding energy, which must be limited due to the degradation of video sequence caused by the same watermark signal. Firstly the video sequences are segmented by each scene, and then the binary watermark pattern is embedded into Discrete Wavelet Transform (DWT) domain of the randomly selected scene blocks. To increase the security, the binary watermark pattern is mapped to a noise like binary pattern using a chaotic mixing method, before its embedding [14]. Then after it, a new two novel schemes to shuffle digital images is introduced. It is different from the conventional schemes based on Standard map, it disorder the pixel positions according to the orbits of the Standard map. The proposed shuffling schemes don't need to discretize the Standard map and own more cipher leys compared with the conventional shuffling scheme based on the discretized Standard map. The shuffling schemes are applied to encrypt image and disorder the host image in watermarking scheme to enhance the robustness against attacks [15]. Digital asset management systems (DAMS) generally handle media data in a compressed and encrypted form. It is sometimes necessary to watermark these compressed encrypted media items in the compressed-encrypted domain itself for tamper detection or ownership declaration or copyright management purposes. It is a challenge to watermark these compressed encrypted streams as the compression process would have packed the information of raw media into a low number of bits and encryption would have randomized the compressed bit stream. Attempting to watermark such a randomized bit stream can cause a dramatic degradation of the media quality. Thus it is necessary to choose an encryption scheme that is both secure and will allow watermarking in a predictable manner in the compressed encrypted domain [3]. Outsourced image recovery service (OIRS), a novel outsourced image recovery service architecture, which exploits different domain technologies and takes security, efficiency, and design complexity into consideration from the very beginning of the service low. Specifically, we choose to design OIRS under the compressed sensing framework, which is known for its simplicity of unifying the traditional sampling and compression for image acquisition. Data owners only need to outsource compressed image samples to cloud for reduced storage overhead. In addition, in OIRS, data users can harness the cloud to securely reconstruct images without revealing information from either the compressed image samples or the underlying image content. OIRS design applied for sparse data, which is the typical application scenario for compressed sensing, and then show its natural extension to the general data for meaningful tradeoffs between efficiency and accuracy [5]. One of watermarking is optical security method. In this, an optical security method for object authentication using photon counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, it can able to encrypt and compress image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system [2].

Since recorded history of information hiding to modern buzz words like watermarking, many theories have been evolving according to the need and advancements. From removable visible watermarking to compress encrypted watermarking there is a lot of issue had address in the past. Now, it is the era of Green technologies. Emergence of big data and its complexities are opening new front for the information security professionals. Some of the major challenges in the near future is as discuss below -
1. The issue of removable visible watermarking in the big data has been rarely studied in the literature and it needs more attention.
2. Reversible data hiding method for encrypted images in the cloud needs more attention to address its authenticity.
3. Issues like missing of DCT coefficients in watermark embedding in the distributed data the major cause of concern.
4. A customized novel lossless (reversible) authentication watermarking framework for medical science data is required.
5. Watermarks are quite robust to routine signal processing, including lossy compression, noise addition, or spatial filtering, so they can effectively be used to carry copyright information that remains embedded in most chains of transmission, storage, and exchange of content.
6. More than one watermarking techniques are required to introduce in a single model for the better result with high degree of robustness.
7. Color image watermarking can be able to accommodate more than one parameter.
8. Confidentiality of the digital content are must be preserve while introducing watermarking scheme.
In this paper we gave broad spectrum of watermarking applications in compressed encrypted images. Big data and related computing are inching towards green computing. Issues in the big data like ownership and security is a great cause of concern for the computer professionals. After this review we come to the following conclusion:-
1. Images are playing very crucial role in the decision making and issues of image authenticity in the Big Data or distributed computing greatly need to be address.
2. Large volumes of images are stored in the compressed or embedded format. Watermarking techniques like novel is need to proposed for the robustness of these images in more customized manner.
3. Watermarking model for the specific real time problem must be customized according to the threat perception. This approach can save cost, power and energy.
4. Authenticity in the financial big data can be preserved by introducing multi-watermarking techniques simultaneously.
5. Ownership of the big data is the great challenge and multi ' watermarking will contribute to address this issue in the long run.
[1] A. Kingston, S. Colosimoy, P. Campisi, F. Autrusseau, 'Lossless Image Compression and selective encryption using a discrete random transform', published in "International Conference on Image Processing, San Antonio, United States, 2007.
[2] A. Markman, B. Javidi, M. Tehranipoor, 'Photon-Counting Security Tagging and Verification Using Optically Encoded QR Codes', Vol. 6, No. 1, February 2014.
[3] A. V. Subramanyam, Sabu Emmanuel, Mohan S. Kankanhalli, 'Robust Watermarking of Compressed and Encrypted JPEG2000 Images', IEEE Transactions on Multimedia, Vol. 14, No. 3, pp. 703 - 716, June 2012.
[4] Chen Tao, Wang Jingchun, 'Image watermarking method using integer-to-integer wavelet transforms', Tsinghus Science and Technology, ISSN 1007-0214 15/22, pp508 ' 512, Volume 7, Number 5 , October 2002.
[5] Cong Wang, Kui Ren, 'Privacy-Assured Outsourcing of Image Reconstruction Service in Cloud', Ieee transactions on emerging topics in computing, Vol. 1, No. 1, pp. 166 ' 177, June 2013.
[6] Deepa Kundur, Kannan Karthik, 'Video Fingerprinting and Encryption Principles for Digital Rights Management', Proceedings of the IEEE, Vol. 92, No. 6, pp. 918 ' 932, June 2004.
[7] Fabien A. P. Petitcolas, Ross J. Anderson, Markus G. Kuhn, 'Information Hiding - A Survey', Proceedings of the IEEE, special issue on protection of multimedia content, Vol. 87(7), pp. ' 1062 - 1078, July 1999.
[8] Federica Battisti, Michela Cancellaro,Giulia Boato, Marco Carli, Alessandro Neri, 'Joint Watermarking and Encryption of Color Images in the Fibonacci-Haar Domain', EURASIP Journal on Advances in Signal Processing, Volume 2009, Article ID 938515, doi:10.1155/ 2009 / 938515.
[9] Hsien-Wen TSENG, Chin-Chen CHANG, 'High Capacity Data Hiding in JPEG-Compressed Images', INFORMATICA, Vol. 15, No. 1, pp. 127'142, 2004.
[10] Ingemar J. Cox, Jean-Paul M. G. Linnartz, 'Some General Methods for Tampering with Watermarks', IEEE Journal on selected areas in communications, Vol. 16, No. 4, pp. 587 - 593, May 1998.
[11] J.F. Delaigle, C. De Vleeschouwer, B. Macq, 'Watermarking algorithm based on a human visual model', Elsevier Science Signal Processing, Vol. 66, pp. 319 ' 335, 1998.
[12] Jasni Zain, Malcolm Clarke, 'Security In Telemedicine: Issues In Watermarking Medical Images', 3rd International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 27-31, 2005.
[13] Mehmet U. Celika, Gaurav Sharma, A.MuratTekalp, Eli Saber, 'Localized Lossless Authentication Watermark (LAW)', Proceedings of SPIE-IS&T Electronic Imaging, SPIE Vol. 5020, pp. 689 ' 698, 2003.
[14] R. Reyes, C. Cruz, M. Nakano-Miyatake, H. P??rez-Meana, 'Digital video watermarking in DWT domain using chaotic mixtures', IEEE latin America transactions, vol. 8, No. 3, june 2010.
[15] Ruisong Ye, Huiqing Huang, 'Application of the Chaotic Ergodicity of Standard Map in Image Encryption and Watermarking', I.J. Image, Graphics and Signal Processing, Vol. 1, pp. 19-29, 2010.
[16] Samia Boucherkha, Mohamed Benmohamed, 'A Lossless Watermarking Based Authentication System For Medical Images', Proceedingd of world Academy of Science, Engineering and Technology, Vol. 1, ISSN 1307-6884, January 2005.
[17] Shiguo Lian, 'Quasi-commutative watermarking and encryption for secure media content distribution', Multimed Tools Appl , Vol. 43, pp. 91'107, 2009.
[18] Shih-Chieh Shie, Shinfeng D. Lin, 'Data hiding based on compressed VQ indices of images', Computer Standards & Interfaces, Vol. 31, pp. 1143'1149, 2009.
[19] W. Puech, M. Chaumont, O. Strauss, 'A Reversible Data Hiding Method for Encrypted Images', published in "IS&T/SPIE Electronic Imaging - Security, Forensics, Steganography, and Watermarking of Multimedia Contents, San Jose, CA : United States, 2008.
[20] Yongjian Hu, Sam Kwong, Jiwu Huang, 'An Algorithm for Removable Visible Watermarking', IEEE Transactions on circuits and systems for video technology, Vol. 16, No. 1, pp. 129 ' 133, January 2006.

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