Defenses against Covert-Communications in Multimedia and Sensor Networks

Steganography and covert-communications represent a great and real threat today more than ever due to the evolution of modern communications. This doctoral work proposes defenses against such covert-communication techniques in two threatening but underdeveloped domains. Indeed, this work focuses on the novel problem of visual sensor network steganalysis but also proposes one of the first solutions against video steganography. The first part of the dissertation looks at covert-communications in videos. The contribution of this study resides in the combination of image processing using motion vector interpolation and non-traditional detection theory to obtain better results in identifying the presence of embedded messages in videos compared to what existing still-image steganalytic solutions would offer. The proposed algorithm called MoViSteg utilizes the specifics of video, as a whole and not as a series of images, to decide on the occurrence of steganography. Contrary to other solutions, MoViSteg is a video-specific algorithm, and not a repetitive still-image steganalysis, and allows for detection of embedding in partially corrupted sequences. This dissertation also lays the foundation for the novel study of visual sensor network steganalysis. We develop three different steganalytic solutions to the problem of covert-communications in visual sensor networks. Because of the inadequacy of the existing steganalytic solutions present in the current research literature, we introduce the novel concept of preventative steganalysis, which aims at discouraging potential steganographic attacks. We propose a set of solutions with active and passive warden scenarii using the material made available by the network. To quantify the efficiency of the preventative steganalysis, a new measure for evaluating the risk of steganography is proposed: the embedding potential which relies on the uncertainty of the image’s pixel values prone to corruption

Enhanced Multimedia Exchanges over the Internet

Although the Internet was not originally designed for exchanging multimedia streams, consumers heavily depend on it for audiovisual data delivery. The intermittent nature of multimedia traffic, the unguaranteed underlying communication infrastructure, and dynamic user behavior collectively result in the degradation of Quality-of-Service (QoS) and Quality-of-Experience (QoE) perceived by end-users. Consequently, the volume of signalling messages is inevitably increased to compensate for the degradation of the desired service qualities. Improved multimedia services could leverage adaptive streaming as well as blockchain-based solutions to enhance media-rich experiences over the Internet at the cost of increased signalling volume. Many recent studies in the literature provide signalling reduction and blockchain-based methods for authenticated media access over the Internet while utilizing resources quasi-efficiently. To further increase the efficiency of multimedia communications, novel signalling overhead and content access latency reduction solutions are investigated in this dissertation including: (1) the first two research topics utilize steganography to reduce signalling bandwidth utilization while increasing the capacity of the multimedia network; and (2) the third research topic utilizes multimedia content access request management schemes to guarantee throughput values for servicing users, end-devices, and the network. Signalling of multimedia streaming is generated at every layer of the communication protocol stack; At the highest layer, segment requests are generated, and at the lower layers, byte tracking messages are exchanged. Through leveraging steganography, essential signalling information is encoded within multimedia payloads to reduce the amount of resources consumed by non-payload data. The first steganographic solution hides signalling messages within multimedia payloads, thereby freeing intermediate node buffers from queuing non-payload packets. Consequently, source nodes are capable of delivering control information to receiving nodes at no additional network overhead. A utility function is designed to minimize the volume of overhead exchanged while minimizing visual artifacts. Therefore, the proposed scheme is designed to leverage the fidelity of the multimedia stream to reduce the largest amount of control overhead with the lowest negative visual impact. The second steganographic solution enables protocol translation through embedding packet header information within payload data to alternatively utilize lightweight headers. The protocol translator leverages a proposed utility function to enable the maximum number of translations while maintaining QoS and QoE requirements in terms of packet throughput and playback bit-rate. As the number of multimedia users and sources increases, decentralized content access and management over a blockchain-based system is inevitable. Blockchain technologies suffer from large processing latencies; consequently reducing the throughput of a multimedia network. Reducing blockchain-based access latencies is therefore essential to maintaining a decentralized scalable model with seamless functionality and efficient utilization of resources. Adapting blockchains to feeless applications will then port the utility of ledger-based networks to audiovisual applications in a faultless manner. The proposed transaction processing scheme will enable ledger maintainers in sustaining desired throughputs necessary for delivering expected QoS and QoE values for decentralized audiovisual platforms. A block slicing algorithm is designed to ensure that the ledger maintenance strategy is benefiting the operations of the blockchain-based multimedia network. Using the proposed algorithm, the throughput and latency of operations within the multimedia network are then maintained at a desired level

Mobile app with steganography functionalities

[Abstract]: Steganography is the practice of hiding information within other data, such as images, audios, videos, etc. In this research, we consider applying this useful technique to create a mobile application that lets users conceal their own secret data inside other media formats, send that encoded data to other users, and even perform analysis to images that may have been under a steganography attack. For image steganography, lossless compression formats employ Least Significant Bit (LSB) encoding within Red Green Blue (RGB) pixel values. Reciprocally, lossy compression formats, such as JPEG, utilize data concealment in the frequency domain by altering the quantized matrices of the files. Video steganography follows two similar methods. In lossless video formats that permit compression, the LSB approach is applied to the RGB pixel values of individual frames. Meanwhile, in lossy High Efficient Video Coding (HEVC) formats, a displaced bit modification technique is used with the YUV components.[Resumo]: A esteganografía é a práctica de ocultar determinada información dentro doutros datos, como imaxes, audio, vídeos, etc. Neste proxecto pretendemos aplicar esta técnica como visión para crear unha aplicación móbil que permita aos usuarios ocultar os seus propios datos secretos dentro doutros formatos multimedia, enviar eses datos cifrados a outros usuarios e mesmo realizar análises de imaxes que puidesen ter sido comprometidas por un ataque esteganográfico. Para a esteganografía de imaxes, os formatos con compresión sen perdas empregan a codificación Least Significant Bit (LSB) dentro dos valores Red Green Blue (RGB) dos seus píxeles. Por outra banda, os formatos de compresión con perdas, como JPEG, usan a ocultación de datos no dominio de frecuencia modificando as matrices cuantificadas dos ficheiros. A esteganografía de vídeo segue dous métodos similares. En formatos de vídeo sen perdas, o método LSB aplícase aos valores RGB de píxeles individuais de cadros. En cambio, nos formatos High Efficient Video Coding (HEVC) con compresión con perdas, úsase unha técnica de cambio de bits nos compoñentes YUV.Traballo fin de grao (UDC.FIC). Enxeñaría Informática. Curso 2022/202

Steganography A Data Hiding Technique

Steganography implements an encryption technique in which communication takes place by hiding information. A hidden message is the combination of a secret message with the carrier message. This technique can be used to hide the message in an image, a video file, an audio file or in a file system. There are large variety of steganography techniques that will be used for hiding secret information in images. The final output image is called as a stego-image which consists of a secret message or information. Imperceptibility, payload, and robustness are three most important parameters for audio steganography. For a more secure approach, encryption can be used, which will encrypt the secret message using a secret key and then sent to the receiver. The receiver after receiving the message then decrypts the secret message to obtain the original one. In this paper, compared steganography with cryptography, which is an encrypting technique and explained how steganography provides better security in terms of hiding the secret message. In this paper, the various techniques are illustrated, which are used in steganography and studying the implementation of those techniques. Also, demonstrated the implementation process of one of the steganography techniques. A comparative analysis is performed between various steganographic tools by using the sample test images and test data. The quality metrics such as PSNR and SSIM are calculated for the final output images which are used for rating the tools. This paper also discusses about the Steganalysis which is known as the process of identifying the use of steganography

CCTV Surveillance System, Attacks and Design Goals

Closed Circuit Tele-Vision surveillance systems are frequently the subject of debate. Some parties seek to promote their benefits such as their use in criminal investigations and providing a feeling of safety to the public. They have also been on the receiving end of bad press when some consider intrusiveness has outweighed the benefits. The correct design and use of such systems is paramount to ensure a CCTV surveillance system meets the needs of the user, provides a tangible benefit and provides safety and security for the wider law-abiding public. In focusing on the normative aspects of CCTV, the paper raises questions concerning the efficiency of understanding contemporary forms of ‘social ordering practices’ primarily in terms of technical rationalities while neglecting other, more material and ideological processes involved in the construction of social order. In this paper, a 360-degree view presented on the assessment of the diverse CCTV video surveillance systems (VSS) of recent past and present in accordance with technology. Further, an attempt been made to compare different VSS with their operational strengths and their attacks. Finally, the paper concludes with a number of future research directions in the design and implementation of VSS

System Steganalysis: Implementation Vulnerabilities and Side-Channel Attacks Against Digital Steganography Systems

Steganography is the process of hiding information in plain sight, it is a technology that can be used to hide data and facilitate secret communications. Steganography is commonly seen in the digital domain where the pervasive nature of media content (image, audio, video) provides an ideal avenue for hiding secret information. In recent years, video steganography has shown to be a highly suitable alternative to image and audio steganography due to its potential advantages (capacity, flexibility, popularity). An increased interest towards research in video steganography has led to the development of video stego-systems that are now available to the public. Many of these stego-systems have not yet been subjected to analysis or evaluation, and their capabilities for performing secure, practical, and effective video steganography are unknown. This thesis presents a comprehensive analysis of the state-of-the-art in practical video steganography. Video-based stego-systems are identified and examined using steganalytic techniques (system steganalysis) to determine the security practices of relevant stego-systems. The research in this thesis is conducted through a series of case studies that aim to provide novel insights in the field of steganalysis and its capabilities towards practical video steganography. The results of this work demonstrate the impact of system attacks over the practical state-of-the-art in video steganography. Through this research, it is evident that video-based stego-systems are highly vulnerable and fail to follow many of the well-understood security practices in the field. Consequently, it is possible to confidently detect each stego-system with a high rate of accuracy. As a result of this research, it is clear that current work in practical video steganography demonstrates a failure to address key principles and best practices in the field. Continued efforts to address this will provide safe and secure steganographic technologies

Classifiers and machine learning techniques for image processing and computer vision

Orientador: Siome Klein GoldensteinTese (doutorado) - Universidade Estadual de Campinas, Instituto da ComputaçãoResumo: Neste trabalho de doutorado, propomos a utilizaçãoo de classificadores e técnicas de aprendizado de maquina para extrair informações relevantes de um conjunto de dados (e.g., imagens) para solução de alguns problemas em Processamento de Imagens e Visão Computacional. Os problemas de nosso interesse são: categorização de imagens em duas ou mais classes, detecçãao de mensagens escondidas, distinção entre imagens digitalmente adulteradas e imagens naturais, autenticação, multi-classificação, entre outros. Inicialmente, apresentamos uma revisão comparativa e crítica do estado da arte em análise forense de imagens e detecção de mensagens escondidas em imagens. Nosso objetivo é mostrar as potencialidades das técnicas existentes e, mais importante, apontar suas limitações. Com esse estudo, mostramos que boa parte dos problemas nessa área apontam para dois pontos em comum: a seleção de características e as técnicas de aprendizado a serem utilizadas. Nesse estudo, também discutimos questões legais associadas a análise forense de imagens como, por exemplo, o uso de fotografias digitais por criminosos. Em seguida, introduzimos uma técnica para análise forense de imagens testada no contexto de detecção de mensagens escondidas e de classificação geral de imagens em categorias como indoors, outdoors, geradas em computador e obras de arte. Ao estudarmos esse problema de multi-classificação, surgem algumas questões: como resolver um problema multi-classe de modo a poder combinar, por exemplo, caracteríisticas de classificação de imagens baseadas em cor, textura, forma e silhueta, sem nos preocuparmos demasiadamente em como normalizar o vetor-comum de caracteristicas gerado? Como utilizar diversos classificadores diferentes, cada um, especializado e melhor configurado para um conjunto de caracteristicas ou classes em confusão? Nesse sentido, apresentamos, uma tecnica para fusão de classificadores e caracteristicas no cenário multi-classe através da combinação de classificadores binários. Nós validamos nossa abordagem numa aplicação real para classificação automática de frutas e legumes. Finalmente, nos deparamos com mais um problema interessante: como tornar a utilização de poderosos classificadores binarios no contexto multi-classe mais eficiente e eficaz? Assim, introduzimos uma tecnica para combinação de classificadores binarios (chamados classificadores base) para a resolução de problemas no contexto geral de multi-classificação.Abstract: In this work, we propose the use of classifiers and machine learning techniques to extract useful information from data sets (e.g., images) to solve important problems in Image Processing and Computer Vision. We are particularly interested in: two and multi-class image categorization, hidden messages detection, discrimination among natural and forged images, authentication, and multiclassification. To start with, we present a comparative survey of the state-of-the-art in digital image forensics as well as hidden messages detection. Our objective is to show the importance of the existing solutions and discuss their limitations. In this study, we show that most of these techniques strive to solve two common problems in Machine Learning: the feature selection and the classification techniques to be used. Furthermore, we discuss the legal and ethical aspects of image forensics analysis, such as, the use of digital images by criminals. We introduce a technique for image forensics analysis in the context of hidden messages detection and image classification in categories such as indoors, outdoors, computer generated, and art works. From this multi-class classification, we found some important questions: how to solve a multi-class problem in order to combine, for instance, several different features such as color, texture, shape, and silhouette without worrying about the pre-processing and normalization of the combined feature vector? How to take advantage of different classifiers, each one custom tailored to a specific set of classes in confusion? To cope with most of these problems, we present a feature and classifier fusion technique based on combinations of binary classifiers. We validate our solution with a real application for automatic produce classification. Finally, we address another interesting problem: how to combine powerful binary classifiers in the multi-class scenario more effectively? How to boost their efficiency? In this context, we present a solution that boosts the efficiency and effectiveness of multi-class from binary techniques.DoutoradoEngenharia de ComputaçãoDoutor em Ciência da Computaçã

Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen