Hunting wild stego images, a domain adaptation problem in digital image forensics

Digital image forensics is a field encompassing camera identication, forgery detection and steganalysis. Statistical modeling and machine learning have been successfully applied in the academic community of this maturing field. Still, large gaps exist between academic results and applications used by practicing forensic analysts, especially when the target samples are drawn from a different population than the data in a reference database. This thesis contains four published papers aiming at narrowing this gap in three different fields: mobile stego app detection, digital image steganalysis and camera identification. It is the first work to explore a way of extending the academic methods to real world images created by apps. New ideas and methods are developed for target images with very rich flexibility in the embedding rates, embedding algorithms, exposure settings and camera sources. The experimental results proved that the proposed methods work very well, even for the devices which are not included in the reference database

Solving the threat of LSB steganography within data loss prevention systems

With the recent spate of data loss breaches from industry and commerce, especially with the large number of Advanced Persistent Threats, companies are increasing their network boundary security. As network defences are enhanced through the use of Data Loss Prevention systems (DLP), attackers seek new ways of exploiting and extracting confidential data. This is often done by internal parties in large-scale organisations through the use of steganography. The successful utilisation of steganography makes the exportation of confidential data hard to detect, equipped with the ability of escaping even the most sophisticated DLP systems. This thesis provides two effective solutions to prevent data loss from effective LSB image steganographic behaviour, with the potential to be applied in industrial DLP systems

Solving the threat of LSB steganography within data loss prevention systems

With the recent spate of data loss breaches from industry and commerce, especially with the large number of Advanced Persistent Threats, companies are increasing their network boundary security. As network defences are enhanced through the use of Data Loss Prevention systems (DLP), attackers seek new ways of exploiting and extracting confidential data. This is often done by internal parties in large-scale organisations through the use of steganography. The successful utilisation of steganography makes the exportation of confidential data hard to detect, equipped with the ability of escaping even the most sophisticated DLP systems. This thesis provides two effective solutions to prevent data loss from effective LSB image steganographic behaviour, with the potential to be applied in industrial DLP systems

Robust steganographic techniques for secure biometric-based remote authentication

Biometrics are widely accepted as the most reliable proof of identity, entitlement to services, and for crime-related forensics. Using biometrics for remote authentication is becoming an essential requirement for the development of knowledge-based economy in the digital age. Ensuring security and integrity of the biometric data or templates is critical to the success of deployment especially because once the data compromised the whole authentication system is compromised with serious consequences for identity theft, fraud as well as loss of privacy. Protecting biometric data whether stored in databases or transmitted over an open network channel is a serious challenge and cryptography may not be the answer. The main premise of this thesis is that Digital Steganography can provide an alternative security solutions that can be exploited to deal with the biometric transmission problem. The main objective of the thesis is to design, develop and test steganographic tools to support remote biometric authentication. We focus on investigating the selection of biometrics feature representations suitable for hiding in natural cover images and designing steganography systems that are specific for hiding such biometric data rather than being suitable for general purpose. The embedding schemes are expected to have high security characteristics resistant to several types of steganalysis tools and maintain accuracy of recognition post embedding. We shall limit our investigations to embedding face biometrics, but the same challenges and approaches should help in developing similar embedding schemes for other biometrics. To achieve this our investigations and proposals are done in different directions which explain in the rest of this section. Reviewing the literature on the state-of-art in steganography has revealed a rich source of theoretical work and creative approaches that have helped generate a variety of embedding schemes as well as steganalysis tools but almost all focused on embedding random looking secrets. The review greatly helped in identifying the main challenges in the field and the main criteria for success in terms of difficult to reconcile requirements on embedding capacity, efficiency of embedding, robustness against steganalysis attacks, and stego image quality. On the biometrics front the review revealed another rich source of different face biometric feature vectors. The review helped shaping our primary objectives as (1) identifying a binarised face feature factor with high discriminating power that is susceptible to embedding in images, (2) develop a special purpose content-based steganography schemes that can benefit from the well-defined structure of the face biometric data in the embedding procedure while preserving accuracy without leaking information about the source biometric data, and (3) conduct sufficient sets of experiments to test the performance of the developed schemes, highlight the advantages as well as limitations, if any, of the developed system with regards to the above mentioned criteria. We argue that the well-known LBP histogram face biometric scheme satisfies the desired properties and we demonstrate that our new more efficient wavelet based versions called LBPH patterns is much more compact and has improved accuracy. In fact the wavelet version schemes reduce the number of features by 22% to 72% of the original version of LBP scheme guaranteeing better invisibility post embedding. We shall then develop 2 steganographic schemes. The first is the LSB-witness is a general purpose scheme that avoids changing the LSB-plane guaranteeing robustness against targeted steganalysis tools, but establish the viability of using steganography for remote biometric-based recognition. However, it may modify the 2nd LSB of cover pixels as a witness for the presence of the secret bits in the 1st LSB and thereby has some disadvantages with regards to the stego image quality. Our search for a new scheme that exploits the structure of the secret face LBPH patterns for improved stego image quality has led to the development of the first content-based steganography scheme. Embedding is guided by searching for similarities between the LBPH patterns and the structure of the cover image LSB bit-planes partitioned into 8-bit or 4-bit patterns. We shall demonstrate the excellent benefits of using content-based embedding scheme in terms of improved stego image quality, greatly reduced payload, reduced lower bound on optimal embedding efficiency, robustness against all targeted steganalysis tools. Unfortunately our scheme was not robust against the blind or universal SRM steganalysis tool. However we demonstrated robustness against SRM at low payload when our scheme was modified by restricting embedding to edge and textured pixels. The low payload in this case is sufficient to embed a secret full face LBPH patterns. Our work opens new exciting opportunities to build successful real applications of content-based steganography and presents plenty of research challenges

Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography

The rapid advancements in digital communication technology and huge increase in computer power have generated an exponential growth in the use of the Internet for various commercial, governmental and social interactions that involve transmission of a variety of complex data and multimedia objects. Securing the content of sensitive as well as personal transactions over open networks while ensuring the privacy of information has become essential but increasingly challenging. Therefore, information and multimedia security research area attracts more and more interest, and its scope of applications expands significantly. Communication security mechanisms have been investigated and developed to protect information privacy with Encryption and Steganography providing the two most obvious solutions. Encrypting a secret message transforms it to a noise-like data which is observable but meaningless, while Steganography conceals the very existence of secret information by hiding in mundane communication that does not attract unwelcome snooping. Digital steganography is concerned with using images, videos and audio signals as cover objects for hiding secret bit-streams. Suitability of media files for such purposes is due to the high degree of redundancy as well as being the most widely exchanged digital data. Over the last two decades, there has been a plethora of research that aim to develop new hiding schemes to overcome the variety of challenges relating to imperceptibility of the hidden secrets, payload capacity, efficiency of embedding and robustness against steganalysis attacks. Most existing techniques treat secrets as random bit-streams even when dealing with non-random signals such as images that may add to the toughness of the challenges.This thesis is devoted to investigate and develop steganography schemes for embedding secret images in image files. While many existing schemes have been developed to perform well with respect to one or more of the above objectives, we aim to achieve optimal performance in terms of all these objectives. We shall only be concerned with embedding secret images in the spatial domain of cover images. The main difficulty in addressing the different challenges stems from the fact that the act of embedding results in changing cover image pixel values that cannot be avoided, although these changes may not be easy to detect by the human eye. These pixel changes is a consequence of dissimilarity between the cover LSB plane and the secretimage bit-stream, and result in changes to the statistical parameters of stego-image bit-planes as well as to local image features. Steganalysis tools exploit these effects to model targeted as well as blind attacks. These challenges are usually dealt with by randomising the changes to the LSB, using different/multiple bit-planes to embed one or more secret bits using elaborate schemes, or embedding in certain regions that are noise-tolerant. Our innovative approach to deal with these challenges is first to develop some image procedures and models that result in increasing similarity between the cover image LSB plane and the secret image bit-stream. This will be achieved in two novel steps involving manipulation of both the secret image and the cover image, prior to embedding, that result a higher 0:1 ratio in both the secret bit-stream and the cover pixels‘ LSB plane. For the secret images, we exploit the fact that image pixel values are in general neither uniformly distributed, as is the case of random secrets, nor spatially stationary. We shall develop three secret image pre-processing algorithms to transform the secret image bit-stream for increased 0:1 ratio. Two of these are similar, but one in the spatial domain and the other in the Wavelet domain. In both cases, the most frequent pixels are mapped onto bytes with more 0s. The third method, process blocks by subtracting their means from their pixel values and hence reducing the require number of bits to represent these blocks. In other words, this third algorithm also reduces the length of the secret image bit-stream without loss of information. We shall demonstrate that these algorithms yield a significant increase in the secret image bit-stream 0:1 ratio, the one that based on the Wavelet domain is the best-performing with 80% ratio.For the cover images, we exploit the fact that pixel value decomposition schemes, based on Fibonacci or other defining sequences that differ from the usual binary scheme, expand the number of bit-planes and thereby may help increase the 0:1 ratio in cover image LSB plane. We investigate some such existing techniques and demonstrate that these schemes indeed lead to increased 0:1 ratio in the corresponding cover image LSB plane. We also develop a new extension of the binary decomposition scheme that is the best-performing one with 77% ratio. We exploit the above two steps strategy to propose a bit-plane(s) mapping embedding technique, instead of bit-plane(s) replacement to make each cover pixel usable for secret embedding. This is motivated by the observation that non-binary pixel decomposition schemes also result in decreasing the number of possible patterns for the three first bit-planes to 4 or 5 instead of 8. We shall demonstrate that the combination of the mapping-based embedding scheme and the two steps strategy produces stego-images that have minimal distortion, i.e. reducing the number of the cover pixels changes after message embedding and increasing embedding efficiency. We shall also demonstrate that these schemes result in reasonable stego-image quality and are robust against all the targeted steganalysis tools but not against the blind SRM tool. We shall finally identify possible future work to achieve robustness against SRM at some payload rates and further improve stego-image quality

New watermarking methods for digital images.

The phenomenal spread of the Internet places an enormous demand on content-ownership-validation. In this thesis, four new image-watermarking methods are presented. One method is based on discrete-wavelet-transformation (DWT) only while the rest are based on DWT and singular-value-decomposition (SVD) ensemble. The main target for this thesis is to reach a new blind-watermarking-method. Method IV presents such watermark using QR-codes. The use of QR-codes in watermarking is novel. The choice of such application is based on the fact that QR-Codes have errors self-correction-capability of 5% or higher which satisfies the nature of digital-image-processing. Results show that the proposed-methods introduced minimal distortion to the watermarked images as compared to other methods and are robust against JPEG, resizing and other attacks. Moreover, watermarking-method-II provides a solution to the detection of false watermark in the literature. Finally, method IV presents a new QR-code guided watermarking-approach that can be used as a steganography as well. --Leaf ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b183575