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ABSTRACT ROBUST DATA HIDING SCHEME WITH TURBO CODES &Uuml / NAL, BariS M.S., Department of Electrical And Electronics Engineering Supervisor: Prof. Dr. R&uuml / yal ERG&Uuml / L December 2005, 127 pages This study describes the design and implementation of a robust data hiding algorithm which is provided by turbo codes. As the digital technology grows up, it is getting easy to copy and distribute multimedia products without getting legal permission. This has forced researchers to study in digital watermarking areas. Along with watermarking researches, data hiding studies have gained interest in the last decade. Different watermark and data hiding algorithms have been proposed considering different requirements and properties such as robustness, fidelity, invisibility and data hiding capacity. In this thesis, robustness of watermarking systems and fidelity requirement in watermark models are considered and use of turbo codes is proposed with data embedding systems to improve system performance in terms of robustness. Fundamental watermarking algorithms in DCT domain are analyzed and simulated. Their performances in terms of robustness are presented. Data hiding algorithm which is based on projection and perturbation in transform domain is implemented in visual C. Then turbo codes are applied to this algorithm to improve system robustness. Improvement provided by turbo codes is demonstrated and compared with other discussed watermarking systems.

The first explored area in this thesis is the proposed data hiding method, TCQ-IS. The method is based on Trellis Coded Quantization (TCQ), whose initial state selection is arbitrary. TCQ-IS exploits this fact to hide data. It is a practical multi-dimensional that eliminates the prohibitive task of designing high dimensional quantizers. The strength and weaknesses of the method are stated by various experiments. The second contribution is the proposed data hiding method, Forbidden Zone Data Hiding (FZDH), which relies on the concept of &ldquo / forbidden zone&rdquo / , where host signal is not altered. The main motive of FZDH is to introduce distortion as much as needed, while keeping a range of host signal intact depending on the desired level of robustness. FZDH is compared against Quantization Index Modulation (QIM) as well as DC-QIM and ST-QIM. FZDH outperforms QIM even in 1-D and DC-QIM in higher dimensions. Furthermore, FZDH is comparable with ST-QIM for certain operation regimes. The final contribution is the video data hiding framework that includes FZDH, selective embedding and Repeat Accumulate (RA) codes. De-synchronization due to selective embedding is handled with RA codes. By means of simple rules applied to the embedded frame markers, certain level of robustness against temporal attacks is introduced. Selected coefficients are used to embed message bits by employing multi-dimensional FZDH. The framework is tested with typical broadcast material against common video processing attacks. The results indicate that the framework can be utilized in real life applications.

Advances in data collection and data storage technologies have given way to the establishment of transactional databases among companies and organizations, as they allow enormous volumes of data to be stored efficiently. Most of the times, these vast amounts of data cannot be used as they are. A data processing should first take place, so as to extract the useful knowledge. After the useful knowledge is mined, it can be used in several ways depending on the nature of the data. Quite often, companies and organizations are willing to share data for the sake of mutual benefit. However, these benefits come with several risks, as problems with privacy might arise, as a result of this sharing. Sensitive data, along with sensitive knowledge inferred from these data, must be protected from unintentional exposure to unauthorized parties. One form of the inferred knowledge is frequent patterns, which are discovered during the process of mining the frequent itemsets from transactional databases. The problem of protecting such patterns is known as the frequent itemset hiding problem. In this thesis, we review several techniques for protecting sensitive frequent patterns in the form of frequent itemsets. After presenting a wide variety of techniques in detail, we propose a novel approach towards solving this problem. The proposed method is an approach that combines heuristics with linear-programming. We evaluate the proposed method on real datasets. For the evaluation, a number of performance metrics are presented. Finally, we compare the results of the newly proposed method with those of other state-of-the-art approaches. / Η ραγδαία εξέλιξη των τεχνολογιών συλλογής και αποθήκευσης δεδομένων οδήγησε στην καθιέρωση των βάσεων δεδομένων συναλλαγών σε οργανισμούς και εταιρείες, καθώς επιτρέπουν την αποδοτική αποθήκευση τεράστιου όγκου δεδομένων. Τις περισσότερες φορές όμως, αυτός ο τεράστιος όγκος δεδομένων δεν μπορεί να χρησιμοποιηθεί ως έχει. Μια πρώτη επεξεργασία των δεδομένων πρέπει να γίνει, ώστε να εξαχθεί η χρήσιμη πληροφορία. Ανάλογα με τη φύση των δεδομένων, αυτή η χρήσιμη πληροφορία μπορεί να χρησιμοποιηθεί στη συνέχεια αναλόγως. Αρκετά συχνά, οι εταιρείες και οι οργανισμοί είναι πρόθυμοι να μοιραστούν τα δεδομένα μεταξύ τους με στόχο το κοινό τους όφελος. Ωστόσο, αυτά τα οφέλη συνοδεύονται με διάφορους κινδύνους, καθώς ενδέχεται να προκύψουν προβλήματα ιδιωτικής φύσης, ως αποτέλεσμα αυτής της κοινής χρήσης των δεδομένων. Ευαίσθητα δεδομένα, μαζί με την ευαίσθητη γνώση που μπορεί να προκύψει από αυτά, πρέπει να προστατευτούν από την ακούσια έκθεση σε μη εξουσιοδοτημένους τρίτους. Μια μορφή της εξαχθείσας γνώσης είναι τα συχνά μοτίβα, που ανακαλύφθηκαν κατά την εξόρυξη συχνών στοιχειοσυνόλων από βάσεις δεδομένων συναλλαγών. Το πρόβλημα της προστασίας συχνών μοτίβων τέτοιας μορφής είναι γνωστό ως το πρόβλημα απόκρυψης συχνών στοιχειοσυνόλων. Στην παρούσα διπλωματική εργασία, εξετάζουμε διάφορες τεχνικές για την προστασία ευαίσθητων συχνών μοτίβων, υπό τη μορφή συχνών στοιχειοσυνόλων. Αφού παρουσιάσουμε λεπτομερώς μια ευρεία ποικιλία τεχνικών απόκρυψης, προτείνουμε μια νέα προσέγγιση για την επίλυση αυτού του προβλήματος. Η προτεινόμενη μέθοδος είναι μια προσέγγιση που συνδυάζει ευρετικές μεθόδους με γραμμικό προγραμματισμό. Για την αξιολόγηση της προτεινόμενης μεθόδου χρησιμοποιούμε πραγματικά δεδομένα. Για τον σκοπό αυτό, παρουσιάζουμε επίσης και μια σειρά από μετρικές αξιολόγησης. Τέλος, συγκρίνουμε τα αποτελέσματα της νέας προτεινόμενης μεθόδου με άλλες κορυφαίες προσεγγίσεις.

Les technologies numériques et du multimédia ont connu de grandes avancées ces dernières années. La chaîne de transmission des images est constituée de plusieurs traitements divers et variés permettant de transmettre un flux de données toujours plus grand avec toujours plus de services à la clé. Nous citons par exemple, la compression, l'augmentation de contenu, la confidentialité, l'intégrité et l'authenticité des images pendant leur transmission. Dans ce contexte, les approches conjointes ont suscité un intérêt certain de la part de la communauté du traitement d'images car elles permettent d'obtenir des systèmes de faible complexité calculatoire pouvant être utilisés dans des applications nécessitant peu de ressources matérielles. La dissimulation de données ou Data Hiding, est l'art de cacher un message dans un support numérique. L'une des branches les plus importantes du data hiding est le tatouage numérique ou watermarking. La marque doit rester présente dans l'image hôte même si celle-ci subit des modifications appelées attaques. La compression d'images a comme objectif de réduire la taille des images stockées et transmises afin d'augmenter la capacité de stockage et de minimiser le temps de transmission. La compression représente une opération incontournable du stockage ou du transfert d'images. Elle est considérée par le data hiding comme une attaque particulièrement destructrice. La norme JPEG2000 est le dernier standard ISO/ITU-T pour le codage des images fixes. Dans cette thèse, nous étudions de manière conjointe la compression avec perte et le data hiding dans le domaine JPEG2000. L'approche conjointe offre de nombreux avantages dont le plus important est que la compression ne constitue plus une attaque vis-à-vis du data hiding. Les contraintes à respecter sont exprimées en termes de compromis à atteindre: compromis entre la quantité d'information insérée (payload), le taux de compression, la distorsion induite par l'insertion du message et la robustesse de la marque dans le cas du tatouage.Nos travaux de recherche ont conduit à l'élaboration de plusieurs schémas conjoints : un schéma conjoint d'insertion de données cachées et deux schémas conjoints de tatouage dans JPEG2000. Tous ces systèmes conjoints reposent sur des stratégies d'insertion informée basées sur la quantification codée par treillis (TCQ). Les propriétés de codage de canal de la TCQ sont exploitées pour pouvoir à la fois quantifier et insérer un message caché (ou une marque) pendant l'étape de quantification de JPEG2000. / Technological advances in the fields of telecommunications and multimedia during the two last decades, derive to create novel image processing services such as copyright protection, data enrichment and information hiding applications. There is a strong need of low complexity applications to perform seveval image processing services within a single system. In this context, the design of joint systems have attracted researchers during the last past years. Data hiding techniques embed an invisible message within a multimedia content by modifying the media data. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. The watermark should be resistant to a variety of manipulations called attacks. The purpose of image compression is to represent images with less data in order to save storage costs or transmission time. Compression is generally unavoidable for transmission or storage purposes and is considered as one of the most destructive attacks by the data hiding. JPEG2000 is the last ISO/ ITU-T standard for still image compression.In this thesis, joint compression and data hiding is investigated in the JPEG2000 framework. Instead of treating data hiding and compression separately, it is interesting and beneficial to look at the joint design of data hiding and compression system. The joint approach have many advantages. The most important thing is that compression is no longer considered as an attack by data hiding.The main constraints that must be considered are trade offs between payload, compression bitrate, distortion induced by the insertion of the hidden data or the watermark and robustness of watermarked images in the watermarking context. We have proposed several joint JPEG2000 compression and data hiding schemes. Two of these joint schemes are watermarking systems. All the embedding strategies proposed in this work are based on Trellis Coded Quantization (TCQ). We exploit the channel coding properties of TCQ to reliably embed data during the quantization stage of the JPEG2000 part 2 codec.

Technological advances have led to the generation of large databases of organizational data recognized as an information-rich, strategic asset for internal analysis and sharing with trading partners. Data mining techniques can discover patterns in large databases including relationships considered strategically relevant to the owner of the data. The frequent item set hiding problem is an area of active research to study approaches for hiding the sensitive knowledge patterns before disclosing the data outside the organization. Several methods address hiding sensitive item sets including an exact approach that generates an extension to the original database that, when combined with the original database, limits the discovery of sensitive association rules without impacting other non-sensitive information. To generate the database extension, this method formulates a constraint optimization problem (COP). Solving the COP formulation is the dominant factor in the computational resource requirements of the exact approach. This dissertation developed heuristics that address the scalability of the exact hiding method. The heuristics are directed at improving the performance of COP solver by reducing the size of the COP formulation without significantly affecting the quality of the solutions generated. The first heuristic decomposes the COP formulation into multiple smaller problem instances that are processed separately by the COP solver to generate partial extensions of the database. The smaller database extensions are then combined to form a database extension that is close to the database extension generated with the original, larger COP formulation. The second heuristic evaluates the revised border used to formulate the COP and reduces the number of variables and constraints by selectively substituting multiple item sets with composite variables. Solving the COP with fewer variables and constraints reduces the computational cost of the processing. Results of heuristic processing were compared with an existing exact approach based on the size of the database extension, the ability to hide sensitive data, and the impact on nonsensitive data.

Approved for public release, distribution is unlimited / The attack of choice for a professional attacker is system subversion: the insertion of a trap door that allows the attacker to bypass an operating system's protection controls. This attack provides significant capabilities and a low risk of detection. One potential design is a trap door that itself accepts new programming instructions. This allows an attacker to decide the capabilities of the artifice at the time of attack rather than prior to its insertion. Early tiger teams recognized the possibility of this design and compared it to the two-card bootstrap loader used in mainframes, since both exhibit the characteristics of compactness and adaptability. This thesis demonstrates that it is relatively easy to create a bootstrapped trap door. The demonstrated artifice consists of 6 lines of C code that, when inserted into the Windows XP operating system, accept additional arbitrary code from the attacker, allowing subversion in any manner the attacker chooses. The threat from subversion is both extremely potent and eminently feasible. Popular risk mitigation strategies that rely on defense-in-depth are ineffective against subversion. This thesis focuses on how the use of the principles of layering, modularity, and information hiding can contribute to high-assurance development methodologies by increasing system comprehensibility. / Civilian, Naval Postgraduate School