Advances in Syndrome Coding based on Stochastic and Deterministic Matrices for Steganography

Steganographie ist die Kunst der vertraulichen Kommunikation. Anders als in der Kryptographie, wo der Austausch vertraulicher Daten für Dritte offensichtlich ist, werden die vertraulichen Daten in einem steganographischen System in andere, unauffällige Coverdaten (z.B. Bilder) eingebettet und so an den Empfänger übertragen. Ziel eines steganographischen Algorithmus ist es, die Coverdaten nur geringfügig zu ändern, um deren statistische Merkmale zu erhalten, und möglichst in unauffälligen Teilen des Covers einzubetten. Um dieses Ziel zu erreichen, werden verschiedene Ansätze der so genannten minimum-embedding-impact Steganographie basierend auf Syndromkodierung vorgestellt. Es wird dabei zwischen Ansätzen basierend auf stochastischen und auf deterministischen Matrizen unterschieden. Anschließend werden die Algorithmen bewertet, um Vorteile der Anwendung von Syndromkodierung herauszustellen

Subliminal channels in post-quantum digital signature schemes

We analyze the digital signatures schemes submitted to NIST\u27s Post-Quantum Cryptography Standardization Project in search for subliminal channels

The role of side information in steganography

Das Ziel digitaler Steganographie ist es, eine geheime Kommunikation in digitalen Medien zu verstecken. Der übliche Ansatz ist es, die Nachricht in einem empirischen Trägermedium zu verstecken. In dieser Arbeit definieren wir den Begriff der Steganographischen Seiteninformation (SSI). Diese Definition umfasst alle wichtigen Eigenschaften von SSI. Wir begründen die Definition informationstheoretisch und erklären den Einsatz von SSI. Alle neueren steganographischen Algorithmen nutzen SSI um die Nachricht einzubetten. Wir entwickeln einen Angriff auf adaptive Steganographie und zeigen anhand von weit verbreiteten SSI-Varianten, dass unser Angriff funktioniert. Wir folgern, dass adaptive Steganographie spieltheoretisch beschrieben werden muss. Wir entwickeln ein spieltheoretisches Modell für solch ein System und berechnen die spieltheoretisch optimalen Strategien. Wir schlussfolgern, dass ein Steganograph diesen Strategien folgen sollte. Zudem entwickeln wir eine neue spieltheoretisch optimale Strategie zur Einbettung, die sogenannten Ausgleichseinbettungsstrategien.The  goal of digital steganography is to hide a secret communication in digital media. The common approach in steganography is to hide the secret messages in empirical cover objects. We are the first to define Steganographic Side Information (SSI). Our definition of SSI captures all relevant properties of SSI. We explain the common usage of SSI. All recent steganographic schemes use SSI to identify suitable areas fot the embedding change. We develop a targeted attack on four widely used variants of SSI, and show that our attack detects them almost perfectly. We argue that the steganographic competition must be framed with means of game theory. We present a game-theoretical framework that captures all relevant properties of such a steganographic system. We instantiate the framework with five different models and solve each of these models for game-theoretically optimal strategies. Inspired by our solutions, we give a new paradigm for secure adaptive steganography, the so-called equalizer embedding strategies

SYNERGY OF BUILDING CYBERSECURITY SYSTEMS

The development of the modern world community is closely related to advances in computing resources and cyberspace. The formation and expansion of the range of services is based on the achievements of mankind in the field of high technologies. However, the rapid growth of computing resources, the emergence of a full-scale quantum computer tightens the requirements for security systems not only for information and communication systems, but also for cyber-physical systems and technologies. The methodological foundations of building security systems for critical infrastructure facilities based on modeling the processes of behavior of antagonistic agents in security systems are discussed in the first chapter. The concept of information security in social networks, based on mathematical models of data protection, taking into account the influence of specific parameters of the social network, the effects on the network are proposed in second chapter. The nonlinear relationships of the parameters of the defense system, attacks, social networks, as well as the influence of individual characteristics of users and the nature of the relationships between them, takes into account. In the third section, practical aspects of the methodology for constructing post-quantum algorithms for asymmetric McEliece and Niederreiter cryptosystems on algebraic codes (elliptic and modified elliptic codes), their mathematical models and practical algorithms are considered. Hybrid crypto-code constructions of McEliece and Niederreiter on defective codes are proposed. They can significantly reduce the energy costs for implementation, while ensuring the required level of cryptographic strength of the system as a whole. The concept of security of corporate information and educational systems based on the construction of an adaptive information security system is proposed. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ How to Cite: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Indexing:                    Розвиток сучасної світової спільноти тісно пов’язаний з досягненнями в області обчислювальних ресурсів і кіберпростору. Формування та розширення асортименту послуг базується на досягненнях людства у галузі високих технологій. Однак стрімке зростання обчислювальних ресурсів, поява повномасштабного квантового комп’ютера посилює вимоги до систем безпеки не тільки інформаційно-комунікаційних, але і до кіберфізичних систем і технологій. У першому розділі обговорюються методологічні основи побудови систем безпеки для об'єктів критичної інфраструктури на основі моделювання процесів поведінки антагоністичних агентів у систем безпеки. У другому розділі пропонується концепція інформаційної безпеки в соціальних мережах, яка заснована на математичних моделях захисту даних, з урахуванням впливу конкретних параметрів соціальної мережі та наслідків для неї. Враховуються нелінійні взаємозв'язки параметрів системи захисту, атак, соціальних мереж, а також вплив індивідуальних характеристик користувачів і характеру взаємовідносин між ними. У третьому розділі розглядаються практичні аспекти методології побудови постквантових алгоритмів для асиметричних криптосистем Мак-Еліса та Нідеррейтера на алгебраїчних кодах (еліптичних та модифікованих еліптичних кодах), їх математичні моделі та практичні алгоритми. Запропоновано гібридні конструкції криптокоду Мак-Еліса та Нідеррейтера на дефектних кодах. Вони дозволяють істотно знизити енергетичні витрати на реалізацію, забезпечуючи при цьому необхідний рівень криптографічної стійкості системи в цілому. Запропоновано концепцію безпеки корпоративних інформаційних та освітніх систем, які засновані на побудові адаптивної системи захисту інформації. ISBN 978-617-7319-31-2 (on-line)ISBN 978-617-7319-32-9 (print) ------------------------------------------------------------------------------------------------------------------ Як цитувати: Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O., Korol, O., Milevskyi, S. et. al.; Yevseiev, S., Ponomarenko, V., Laptiev, O., Milov, O. (Eds.) (2021). Synergy of building cybersecurity systems. Kharkiv: РС ТЕСHNOLOGY СЕNTЕR, 188. doi: http://doi.org/10.15587/978-617-7319-31-2 ------------------------------------------------------------------------------------------------------------------ Індексація:                 &nbsp

Exploring variability in medical imaging

Although recent successes of deep learning and novel machine learning techniques improved the perfor- mance of classification and (anomaly) detection in computer vision problems, the application of these methods in medical imaging pipeline remains a very challenging task. One of the main reasons for this is the amount of variability that is encountered and encapsulated in human anatomy and subsequently reflected in medical images. This fundamental factor impacts most stages in modern medical imaging processing pipelines. Variability of human anatomy makes it virtually impossible to build large datasets for each disease with labels and annotation for fully supervised machine learning. An efficient way to cope with this is to try and learn only from normal samples. Such data is much easier to collect. A case study of such an automatic anomaly detection system based on normative learning is presented in this work. We present a framework for detecting fetal cardiac anomalies during ultrasound screening using generative models, which are trained only utilising normal/healthy subjects. However, despite the significant improvement in automatic abnormality detection systems, clinical routine continues to rely exclusively on the contribution of overburdened medical experts to diagnosis and localise abnormalities. Integrating human expert knowledge into the medical imaging processing pipeline entails uncertainty which is mainly correlated with inter-observer variability. From the per- spective of building an automated medical imaging system, it is still an open issue, to what extent this kind of variability and the resulting uncertainty are introduced during the training of a model and how it affects the final performance of the task. Consequently, it is very important to explore the effect of inter-observer variability both, on the reliable estimation of model’s uncertainty, as well as on the model’s performance in a specific machine learning task. A thorough investigation of this issue is presented in this work by leveraging automated estimates for machine learning model uncertainty, inter-observer variability and segmentation task performance in lung CT scan images. Finally, a presentation of an overview of the existing anomaly detection methods in medical imaging was attempted. This state-of-the-art survey includes both conventional pattern recognition methods and deep learning based methods. It is one of the first literature surveys attempted in the specific research area.Open Acces

Application and Theory of Multimedia Signal Processing Using Machine Learning or Advanced Methods

This Special Issue is a book composed by collecting documents published through peer review on the research of various advanced technologies related to applications and theories of signal processing for multimedia systems using ML or advanced methods. Multimedia signals include image, video, audio, character recognition and optimization of communication channels for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition. Academics and colleagues who are interested in these topics will find it interesting to read

Statistical pattern recognition for audio-forensics : empirical investigations on the application scenarios audio steganalysis and microphone forensics

Magdeburg, Univ., Fak. für Informatik, Diss., 2013von Christian Krätze

Faculty Publications and Creative Works 2004

Faculty Publications & Creative Works is an annual compendium of scholarly and creative activities of University of New Mexico faculty during the noted calendar year. Published by the Office of the Vice President for Research and Economic Development, it serves to illustrate the robust and active intellectual pursuits conducted by the faculty in support of teaching and research at UNM