| Internet and wireless networks offer ubiquitous channels to deliver and to exchange information. Since the rise of the Internet, one of the most important factors of information technology and communication has been the security of information. The applications of information hiding are used by military and intelligence agencies, illicit and criminal activities, and healthcare and by other parties where data security is important. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. Imperceptibility, robustness against moderate processing such as image compression, and capacity (the amount of data that can be hidden inside the image) are the basic but rather conflicting requirements for many data hiding applications. Hiding information inside the image may damage the image quality; however, using appropriate techniques may increase the embedding capacity without noticeable damage to the image content.The ideas of information hiding can be traced back to a few thousand years ago. Simply obscuring the content of messages by encryption is not always adequate in practice. In many rivalry environments, concealing the existence of communication is desirable to avoid suspicion from adversaries. The word "steganography", which originated from Greek and is still in use today, literally means "covered writing". Many stories of covert communications have been passed for generations, but they were mainly used by military and intelligence agencies. Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is to always conceal the very existence of the embedded data.Rather than playing with the terminologies, this thesis uses the three terms Cryptography, Steganography and Watermarking. The embedded data, usually called watermark(s), can be used for various purposes, each of which is associated with different robustness, security, and embedding capacity requirements. The principal advantage of data hiding versus other solutions is its ability to associate secondary data with the primary media in a seamless way. As we shall see later in this thesis, the seamless association is desirable in many applications. For example, compared with cryptographic encryptions, the embedded watermarks can travel with the host media and assume their protection functions even after decryption. With the only exception of visible watermarks, the secondary data are expected to be imperceptible.Three techniques are interlinked; steganography, watermarking and cryptography, under the term of information hiding. The standard and concept of "What You See Is What You Get(WYSIWYG)", which we encounter sometimes while printing images or other materials, is no longer precise and would not fool a steganographer as it does not always hold true. Images can be more than what we see with our Human Visual System (HVS); hence, they can convey more than merely1000words. Intuitively, this work makes use of some terms commonly used by steganography and watermarking communities. The term "cover image" will be used throughout this dissertation to describe the image designated to carry the embedded bits. The image with embedded data, called herein payload, is known as a "stegoimage". Further "steganalysis" or "attacks" refer to different image processing and statistical analysis approaches that aim to break or attack steganography algorithms.From this brief overview the reader may have already noticed another fundamental difference between steganography and watermarking. The information hidden by a Watermarking system is always associated to the digital object to be protected or to its owner while steganographic systems just hide any information. The "robustness" criteria are also different, since steganography is mainly concerned with detection of the hidden message while watermarking concerns potential removal by a pirate. Finally, steganographic communications are usually point-to-point (between sender and receiver) while watermarking techniques are usually one-to-many.There are many ways to categorize data hiding techniques. A straightforward classification is according to the type of primary multimedia sources, giving us data hiding systems for perceptual and non-perceptual sources. This thesis is concerned with perceptual sources, including, binary image, and color or grayscale image. Among digital sources, the major difference between perceptual and non-perceptual data is that the non-perceptual data, like text and executable codes, usually requires lossless processing, transmission and storage. Flipping a single bit may lead to different meaning. Perceptual data, however, has a perceptual tolerance range, which allows minor change before being noticed by humans. This perceptual property enables controllable amount of perceptual degradation.In terms of perceptibility, data hiding techniques can be classified into two groups; perceptible and imperceptible hiding. Perceptible watermarks are mainly used in image and video. A visually meaningful pattern, such as a logo, is overlaid on an image or video, which is essentially an image editing or synthesis problem. The visible watermarks explicitly exhibit the copyright, ownership information, or access control policies so as to discourage the misuse of the watermarked imagesSemitransparent logos are commonly added to TV programs by broadcasting networks and to the preview images accessible via World Wide Web by copyright holders. The majority of current data hiding research concerns with imperceptible watermarking. As we mentioned earlier, perceptual models need to be explored to ensure the changes imposed by an embedding system are imperceptible to retain the perceptual quality and value of the multimedia sources.Application domain is another criterion to categorize data hiding techniques. Classic applications include ownership protection, authentication, fingerprinting, copy/access control, and annotation. We shall briefly explain the design requirement of each application:1. Ownership Protection:a watermark indicating ownership is embedded in the multimedia source. The watermark, known only to the copyright holder, is expected to survive common processing and intentional attack so that the owner can show the presence of this watermark in case of dispute to demonstrate his/her ownership. The detection should have as little ambiguity and false alarm as possible. The total embedding capacity, namely, the number of bits that can be embedded and extracted with small probability of error does not have to be high in most scenarios.2. Authentication or Tampering Detection:a set of secondary data is embedded in the multimedia source beforehand, and later is used to determine whether the host media is tampered or not. The robustness against removing the watermark or making it undetectable is not a concern as there is no such incentive from the attacker’s point of view. However, forging a valid authentication watermark in an unauthorized or tampered media source must be prevented. In practical applications, it is also desirable to locate the tampering, and to distinguish some changes (such as the non-content change incurred by moderate lossy compression) from some other changes (such as content tampering). The embedding capacity has to be high in general to accommodate these needs. The detection should be performed without the original unwatermarked copy because either this original is unavailable or its integrity has not been established yet. This kind of detection is usually called non-coherent detection or blind detection.3. Fingerprinting or labeling:the watermark in this application is used to trace the originator or recipients of a particular copy of multimedia source. For example, different watermarks are embedded in different copies of multimedia sources before distributing to a number of recipients. The robustness against obliterating and the ability to convey a non-trivial number of bits are required.4. Copy Control&Access Control:the embedded watermark in this case represents certain copy control or access control policy. A watermark detector is usually integrated in a recording/playback system, like the proposed DVD copy control and the on-going SDMI activities. Upon detection, the policy is enforced by directing certain hardware or software actions such as enabling or disabling a recording module. The robustness against removal, the ability of blind detection, and the capability of conveying a non-trivial number of bits are required.5. Annotation:the embedded watermark in this application is expected to convey as many bits as possible without the use of original unmarked copy in detection. While the robustness against intentional attack is not required, a certain degree of robustness against common processing, like lossy compression, may be desired.Visual cryptography is a method of sharing a secret image among a group of participants, where certain group of participants are defined as qualified and may combine their shares of the secret image to obtain the original secret image, but certain other groups are defined as forbidden, even if they combine knowledge about their parts of secret image, they cannot obtain any information on the original secret image. The image is composed of black and white pixels. Pixel is the term most widely used to denote the elements of a digital image. To encode the secret image, each pixel is divided into m sub-pixels, some of which are black and some of which are white. These sub-pixels are so small that the eye averages them to some shade of grey and that is called spatial frequency resolution. Each participant’s share of the image (transparency) looks as a random distribution of black and white pixels. To combine shares, participants simply stack their transparencies. The parameter m is called the pixel expansion, making this parameter small means saving storage space and reduction in the transmission time.Visual cryptography is interesting because decryption requires no computation, but instead is done by the human visual system. The image is reconstructed by combining shares of a qualified group of participants and is not identical to the secret image. The pixels of the secret image that were white are a lighter shade of grey than the pixels of the image that were black, and the difference in the darkness of the black and white pixels is a parameter called contrast. Ideally, highest contrast gives better results in term of ease of differentiation the black and white areas.The security of the sharing scheme depends on the information that can be obtained about the secret image from each single share or from any forbidden set of participant’s shares. This involves how far the sub pixels are randomly distributed in each share and in the resulting image of combined forbidden shares.Imperceptibility, robustness against moderate processing such as compression, and capacity (the ability to hide many bits) are the basic but rather conflicting requirements for many data hiding applications. In addition, a few other important problems encountered in practice, such as the uneven embedding capacity for image and the perceptual models for binary images, have received little attention in literature. The visual requirements model, which is called magic triangle. The first requirement, called capacity or also embedding payload, is determined by the number of secret bits embedded in each cover pixel. A higher capacity allows much more secret data to be inserted into the cover image. The second requirement, named imperceptibility, is usually calculated by peak signal-to-noise ratio (PSNR). When the difference between the cover image and the stegoimage is small, the PSNR value is high. Thus, the stegoimage quality is considered to be good when the imperceptibility is high. The last requirement is called robustness, which prevents the secret data from being attacked or stolen from the image. However, only the complex part of the image holds added information. There are many reasons to hide data but they all boil down to the desire to prevent unauthorized persons from becoming aware of the existence of a message.The many advantages of digital information have generated new challenges and new opportunities for innovation. Internet offers ubiquitous channels to deliver and to exchange information. The security and fair use of the multimedia data, as well as the fast delivery of multimedia content to a variety of end users/devices with guaranteed quantity and security are important yet challenging topics. The solutions to these problems will not only contribute to our understanding of this fast moving complex technology, but also offer new economic opportunities to be explored. With the advent of the Internet and the widespread use of digital media, information hiding has become especially important to people interested in either communicating secretly or protecting their digital works from unauthorized copying. Information hiding comprises such diverse topics as steganography, anonymity, cover channels and copyright marking. Most of these topics have a long history and have found their way into everyday life and the popular culture. Many techniques have been proposed for a variety of applications. Data hiding is also found useful as a general tool to send side information in multimedia communications for achieving additional functionalities or enhancing performance.There are several reasons for limiting survey of information hiding to images only. Images are widespread on the Internet and can be used as carrier objects without raising much suspicion. They come in many formats, although JPEG and GIF are most dominant.(Conversely, audio files are usually in the MPEG3format and videos are in either MPEG1or MPEG2formats.). Finally, most image files are quite large and have a lot of capacity for modification without noticeable damage to the image content.Types of image data are divided into two primary categories:bitmap and vector. Bitmap images (also called raster images) can be presented by image model I(r,c), each pixel data has a corresponding brightness value stored in some file format. Vector images refer to methods of representing lines, curves, and shapes by storing only the key points (This is mainly used with computer graphic rather than natural images). These key points are sufficient to define the shapes, and the process of turning these into an image is called rendering. After the image has been rendered, it can be thought of as being in bitmap format where each pixel has specific values associated with it.Some of the bitmap images are compressed, so that the I(r, c) values are not directly available until the file is decompressed. In general, these types of images contain both header information and the raw pixel data. The header must contain information regarding to the number of rows (height), the number of rows (height), the number of columns (width), the number of bands, the number of bits per pixel, the file type. Additionally, with some of the more complex file formats, the header may contain information about the type of compression used and other necessary parameters to create the images, I(r, c).The simplest file formats are the BIN and the PPM file formats. The BIN format is simply the raw image data I(r, c). This file contains no header information; the user must know the necessary parameters-size, number of bands, and bits per pixel-to use the file as image. The PPM formats are widely used, and a set of conversion utilities is freely available (bmpplus). They basically contain raw image data with the simplest header possible. The PPM format includes PBM (binary), PGM (gray-scale), PPM (color), and PNM (handles any of the previous types). The headers for these image file formats contain a magic number that identifies the file type, the image height and width, the number of bands, and the maximum brightness value (which determines the required number of bits per pixel for each band).JPEG File Interchange Format (JFIF) is rapidly becoming a standard that allows images compressed with the JPEG algorithm to be used in many different computer platforms. The JFIF files have a Start of Image (SOI) and an application marker that serve as a file header. JPEG image compression is being used extensively on the WWW and is expected to become the standard for many applications.Two formats that were initially computer specific, but have become commonly used throughout the industry, are the Sun Raster and the SGI (Silicon Graphic, Inc.) file formats. The Sun Raster file format is much more ubiquitous than the SGI, but SGI has become the leader in state-of-the-art graphics computers. The SGI format handles up to16million colors and supports RLE compression. The SGI image header is512byte (with the majority of the bytes not used, presumably for future extensions) followed by the image data. The Sun Raster format is defined to allow for any number of bits per pixel and also support RLE compression and color LUTs. It has a32-byte header, followed by the image dataAlthough steganography is an ancient subject, the modern formulation of it is often given in terms of the prisoner’s problem proposed by Simmon, where two inmates wish to communicate in secret to hatch an escape plan. All of their communication passes through a warden who will throw them in solitary confinement should she suspect any covert communication.The warden, who is free to examine all communication exchanged between the inmates, can either be passive or active. A passive warden simply examines the communication to try and determine if it potentially contains secret information. If she suspects a communication to contain hidden information, a passive warden takes note of the detected covert communication, reports this to some outside party and lets the message through without blocking it. An active warden, on the other hand, will try to alter the communication with the suspected hidden information deliberately, in order to remove the information.Almost all digital file formats can be used for steganography, but the formats that are more suitable are those with a high degree of redundancy. Redundancy can be defined as the bits of an object that provide accuracy far greater than necessary for the object’s use and display. The redundant bits of an object are those bits that can be altered without the alteration being detected easily. Image and audio files especially comply with this requirement, while research has also uncovered other file formats that can be used for information hiding.Hiding information in text is historically the most important method of steganography. An obvious method was to hide a secret message in every nth letter of every word of a text message. It is only since the beginning of the Internet and all the different digital file formats that is has decreased in importance. Text steganography using digital files is not used very often since text files have a very small amount of redundant data. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography.To hide information in audio files similar techniques are used as for image files. One different technique unique to audio steganography is masking, which exploits the properties of the human ear to hide information unnoticeably. A faint, but audible, sound becomes inaudible in the presence of another louder audible sound. This property creates a channel in which to hide information. Although nearly equal to images in steganographic potential, the larger size of meaningful audio files makes them less popular to use than images.Basically, the purpose of cryptography and steganography is to provide secret communication. However, steganography is not the same as cryptography. Cryptography hides the contents of a secret message from malicious people, whereas steganography even conceals the existence of the message. Steganography must not be confused with cryptography, where we transform the message so as to make it meaning obscure to a malicious people who intercept it. Therefore, the definition of breaking the system is different. In cryptography, the system is broken when the attacker can read the secret message. Breaking a steganographic system needs the attacker to detect that steganography that has been used and he has the ability to be able to read the embedded message.In cryptography, the structure of a message is scrambled to make it meaningless and unintelligible unless the decryption key is available. It makes no attempt to disguise or hide the encoded message. Basically, cryptography offers the ability of transmitting information between persons in a way that prevents a third party from reading it. Cryptography can also provide authentication for verifying the identity of someone or something. In contrast, steganography does not alter the structure of the secret message, but hides it inside a coverimage so it cannot be seen. A message in cipher text, for instance, might arouse suspicion on the part of the recipient while an "invisible" message created with steganographic methods will not. In other word, steganography prevents an unintended recipient from suspecting that the data exists. In addition, the security of classical steganography system relies on secrecy of the data encoding system. Once the encoding system is known, the steganography system is defeated.It is possible to combine the techniques by encrypting message using cryptography and then hiding the encrypted message using steganography. The resulting stegoimage can be transmitted without revealing that secret information is being exchanged. Furthermore, even if an attacker was to defeat the steganographic technique and detect the message from the stegoobject, he would still require the cryptographic decoding key to decipher the encrypted message.An effective and secure protection of sensitive information is the primary concern in communication systems or network storage systems. Nevertheless, it is also important for any information process to ensure data is not being tampered with. Encryption methods are one of the popular approaches to ensure the integrity and confidentiality of the protected information. However, one of the critical vulnerabilities of encryption techniques is protecting the information from being exposed. To address these reliability problems, especially for large information content items such as secret images (satellite photos or medical images), an image secret sharing schemes (SSS) is a good alternative to remedy these types of vulnerabilitiesSuppose a bank vault must be opened every day. Although the bank employs three senior tellers, management does not want to entrust any individual with the combination. Hence, bank management would like a vault-access system that requires any two of the three senior tellers. This problem can be solved using a secret sharing scheme called two-out-of-three threshold scheme.A secret sharing scheme is an intellectual candidate for ensuring secrets as cryptographic keys transmit via internet. There are many application areas where secrets need to be shared. Some of these application areas are the following:1. Key escrow in public key cryptosystems.2. Revocable anonymity in electronic money.3. Authorization for critical operations, i.e. missile launches, etc.There are many criteria to classify secret sharing schemes. These criteria are based on the type of the secret, process of recovery, and the accuracy and quality of the recovered secret. This classification can be based on:1. Secret Type.In this classification, there are two types of secret sharing schemes: The old traditional secret sharing:Here, the secret can only represent number. The recovery of the secret involves computations. Since the invention in1979, secret sharing schemes have been extensively investigated. In particular, much work was done on the required length of the shares relative to the secret size. It is a well known basic fact that shares of a secret have to be at least of the size of the secret itself, and most of the work on share sizes investigates when this lower bound can be achieved or must be exceeded for different kinds of schemes. Having shares of the size of the secret is not a serious problem as long as these secrets are short, e.g. short secret key, as most traditional applications require. However, this effect of information replication among the participants of a distributed environment can be very space and communication inefficient if the secret is a large confidential file, a long message to be transmitted over unreliable links, or a secret data base shared by several servers. Applications like these are becoming more and more necessary. Visual Secret Sharing schemes:The secret represents image. The first time for such scheme was introduced1994.2. The Quality of Recovered ImageThe accuracy and the quality of the recovered secret image classify v secret sharing schemes into two categories:Lossless visual secret sharing schemes:The recovered image from qualified set of shares must be identical to the original secret image.Lossy visual secret sharing schemes:The schemes attempt to eliminate imperceptibly information of image and minimize the size in bandwidth and storage space3. The computational Power for Decoding SharesAccording to this criteria, generally visual secret scheme fall into three main categories:(1) Visual cryptography (VC-based) visual secret sharing schemes: Secret image sharing called visual cryptography where the recovery process of the secret image requires no computations.(2) Variant Visual Secret Sharing (VVSS-based):Quality of the recovered secret image improves dramatically by extending visual cryptography to adopt low computation operations (e.g., logical AND, OR and XOR) in decoding.(1) Interpolation method (IM-based) schemes:Secret sharing schemes in this category encode and decode image using the most computational power (compared with the above two categories).Information hiding is mostly used in different application areas like, the business world, Steganography can be used to hide a secret chemical formula or plans for a new invention. Steganography can also be used in the non-commercial sector to keep private digital information protected for a number of purposes such as secret data hiding and copyright protection. It can be used for Data authentication, ensuring authenticated data availability for academic usage, monitoring of data piracy, labeling electronic data/contents, ownership identification, providing confidentiality and integrity enhancement control of electronic data piracy etc.Unobtrusive communications are required by military and intelligence agencies:even if the content is encrypted, the detection of a signal on a modern battlefield may lead rapidly to an attack on the signaler. For this reason, military communications use techniques such as spread spectrum modulation or meteor scatter transmission to make signals hard for the enemy to detect or jam.Criminals also place great value on unobtrusive communications and their preferred technologies include prepaid mobile phones and hacked corporate Switch boards through which calls can be rerouted. As a side effect, law enforcement and counter intelligence agencies are interested in understanding these technologies and their weaknesses, so as to detect and trace hidden messages.Information hiding techniques also underlie many attacks on "multilevel secure" systems used by military organizations. A virus or other malicious code propagates itself from "low security" to "high security" levels and then signals data downwards using a covert channel in the operating system or by hiding information directly in data that may be declassified.hiding techniques can also be used in situations where plausible deniability is required. The obvious motivation for plausible deniability is when the two communicating parties are engaged in an activity which is somehow illicit, and they wish to avoid being caught but more legitimate motives include fair voting, personal privacy, or limitation of liability.Anonymous communications, including anonymous remailers and Web proxies, are required by legitimate users to vote privately in online elections, make political claims, consume sexual material, preserve online free speech, or to use digital cash. But the same techniques can be abused for defamation, blackmail, or unsolicited commercial mailing. The ethical positions of the players in the information hiding game are not very clear; therefore, the design of techniques providing such facilities requires careful thought about the possible abuses, which might be non-obvious.The healthcare industry, and especially medical imaging systems, may benefit from information hiding techniques. They use standards such as DICOM (digital imaging and communications in medicine) which separates image data from the caption, such as the name of the patient, the date, and the name of the physician. Sometimes the link between image and patient is lost, thus, embedding the name of the patient in the image could be a useful safety measure. Another emerging technique related to the healthcare industry is hiding messages in DNA sequences. This could be used to protect intellectual property in medicine, molecular biology or genetics.A number of other applications of information hiding have been proposed in the context of multimedia applications. In many cases they can use techniques already developed for copyright marking directly; in others, they can use adapted schemes or shed interesting light on technical issues. The application of information hiding includes automatic monitoring of copyrighted material on the Web, automatic audit of radio transmissions, Data augmentation, Tamper proofing.The purpose of this research is to investigate the image information hiding issues associated with estimating the capacity of the embedding process in addition to develop a visual secret sharing scheme. The contributions of this dissertation are described as follows:Firstly, In order to enhance the security of the information, we proposed a novel and effective visual secret sharing scheme (VSS) based on the use of pseudo random number generator (PRNG). The PRNG has very long periods to ensure unrepeated pattern, meets the known conditions for randomness. The random generator devised here will have new features, such as, using variable permutation, and a system of linear feedback shift registers in addition to nonlinear functions. The proposed scheme is developed to be perfect (the scheme is called perfect if any non-qualified (forbidden) subset has absolutely no information about the shared secret); in our system, any share will not reveal any unintended information about the secret image. The proposed scheme is intended to achieve optimal pixel expansion, which leads to huge reduction in the space needed to store shares and improves the speed of transmission channel of digital information. The shares of the visual cryptography schemes are to be used mainly in digital networking and they are transmitted on air. As the shares become smaller they get transmitted faster and save storage media space.Second, the basic idea is to build image a steganography technique to hide information in the frequency domain by altering the magnitude of all DCT coefficients to increase the embedding capacity. To achieve that we used Discreet Cosine transformation (DCT) to transform original image (cover image) blocks from spatial domain to frequency domain. Huffman encoding is performed on the secret image before it is embedded in the frequency domain and the four tier storage procedure is applied to increase the security of the secret image. LSB embedding mechanism is perfect in deceiving the HVS; however, it has weak resistance to attacks. We applied a Consistent Bit Length embedding mechanism in frequency domain to increase the embedding capacity without affecting security or quality of the cover image. We n... |
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