Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

End-to-end security in active networks

Active network solutions have been proposed to many of the problems caused by the increasing heterogeneity of the Internet. These ystems allow nodes within the network to process data passing through in several ways. Allowing code from various sources to run on routers introduces numerous security concerns that have been addressed by research into safe languages, restricted execution environments, and other related areas. But little attention has been paid to an even more critical question: the effect on end-to-end security of active flow manipulation. This thesis first examines the threat model implicit in active networks. It develops a framework of security protocols in use at various layers of the networking stack, and their utility to multimedia transport and flow processing, and asks if it is reasonable to give active routers access to the plaintext of these flows. After considering the various security problem introduced, such as vulnerability to attacks on intermediaries or coercion, it concludes not. We then ask if active network systems can be built that maintain end-to-end security without seriously degrading the functionality they provide. We describe the design and analysis of three such protocols: a distributed packet filtering system that can be used to adjust multimedia bandwidth requirements and defend against denial-of-service attacks; an efficient composition of link and transport-layer reliability mechanisms that increases the performance of TCP over lossy wireless links; and a distributed watermarking servicethat can efficiently deliver media flows marked with the identity of their recipients. In all three cases, similar functionality is provided to designs that do not maintain end-to-end security. Finally, we reconsider traditional end-to-end arguments in both networking and security, and show that they have continuing importance for Internet design. Our watermarking work adds the concept of splitting trust throughout a network to that model; we suggest further applications of this idea

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Applications de la représentation parcimonieuse perceptuelle par graphe de décharges (Spikegramme) pour la protection du droit d’auteur des signaux sonores

Chaque année, le piratage mondial de la musique coûte plusieurs milliards de dollars en pertes économiques, pertes d’emplois et pertes de gains des travailleurs ainsi que la perte de millions de dollars en recettes fiscales. La plupart du piratage de la musique est dû à la croissance rapide et à la facilité des technologies actuelles pour la copie, le partage, la manipulation et la distribution de données musicales [Domingo, 2015], [Siwek, 2007]. Le tatouage des signaux sonores a été proposé pour protéger les droit des auteurs et pour permettre la localisation des instants où le signal sonore a été falsifié. Dans cette thèse, nous proposons d’utiliser la représentation parcimonieuse bio-inspirée par graphe de décharges (spikegramme), pour concevoir une nouvelle méthode permettant la localisation de la falsification dans les signaux sonores. Aussi, une nouvelle méthode de protection du droit d’auteur. Finalement, une nouvelle attaque perceptuelle, en utilisant le spikegramme, pour attaquer des systèmes de tatouage sonore. Nous proposons tout d’abord une technique de localisation des falsifications (‘tampering’) des signaux sonores. Pour cela nous combinons une méthode à spectre étendu modifié (‘modified spread spectrum’, MSS) avec une représentation parcimonieuse. Nous utilisons une technique de poursuite perceptive adaptée (perceptual marching pursuit, PMP [Hossein Najaf-Zadeh, 2008]) pour générer une représentation parcimonieuse (spikegramme) du signal sonore d’entrée qui est invariante au décalage temporel [E. C. Smith, 2006] et qui prend en compte les phénomènes de masquage tels qu’ils sont observés en audition. Un code d’authentification est inséré à l’intérieur des coefficients de la représentation en spikegramme. Puis ceux-ci sont combinés aux seuils de masquage. Le signal tatoué est resynthétisé à partir des coefficients modifiés, et le signal ainsi obtenu est transmis au décodeur. Au décodeur, pour identifier un segment falsifié du signal sonore, les codes d’authentification de tous les segments intacts sont analysés. Si les codes ne peuvent être détectés correctement, on sait qu’alors le segment aura été falsifié. Nous proposons de tatouer selon le principe à spectre étendu (appelé MSS) afin d’obtenir une grande capacité en nombre de bits de tatouage introduits. Dans les situations où il y a désynchronisation entre le codeur et le décodeur, notre méthode permet quand même de détecter des pièces falsifiées. Par rapport à l’état de l’art, notre approche a le taux d’erreur le plus bas pour ce qui est de détecter les pièces falsifiées. Nous avons utilisé le test de l’opinion moyenne (‘MOS’) pour mesurer la qualité des systèmes tatoués. Nous évaluons la méthode de tatouage semi-fragile par le taux d’erreur (nombre de bits erronés divisé par tous les bits soumis) suite à plusieurs attaques. Les résultats confirment la supériorité de notre approche pour la localisation des pièces falsifiées dans les signaux sonores tout en préservant la qualité des signaux. Ensuite nous proposons une nouvelle technique pour la protection des signaux sonores. Cette technique est basée sur la représentation par spikegrammes des signaux sonores et utilise deux dictionnaires (TDA pour Two-Dictionary Approach). Le spikegramme est utilisé pour coder le signal hôte en utilisant un dictionnaire de filtres gammatones. Pour le tatouage, nous utilisons deux dictionnaires différents qui sont sélectionnés en fonction du bit d’entrée à tatouer et du contenu du signal. Notre approche trouve les gammatones appropriés (appelés noyaux de tatouage) sur la base de la valeur du bit à tatouer, et incorpore les bits de tatouage dans la phase des gammatones du tatouage. De plus, il est montré que la TDA est libre d’erreur dans le cas d’aucune situation d’attaque. Il est démontré que la décorrélation des noyaux de tatouage permet la conception d’une méthode de tatouage sonore très robuste. Les expériences ont montré la meilleure robustesse pour la méthode proposée lorsque le signal tatoué est corrompu par une compression MP3 à 32 kbits par seconde avec une charge utile de 56.5 bps par rapport à plusieurs techniques récentes. De plus nous avons étudié la robustesse du tatouage lorsque les nouveaux codec USAC (Unified Audion and Speech Coding) à 24kbps sont utilisés. La charge utile est alors comprise entre 5 et 15 bps. Finalement, nous utilisons les spikegrammes pour proposer trois nouvelles méthodes d’attaques. Nous les comparons aux méthodes récentes d’attaques telles que 32 kbps MP3 et 24 kbps USAC. Ces attaques comprennent l’attaque par PMP, l’attaque par bruit inaudible et l’attaque de remplacement parcimonieuse. Dans le cas de l’attaque par PMP, le signal de tatouage est représenté et resynthétisé avec un spikegramme. Dans le cas de l’attaque par bruit inaudible, celui-ci est généré et ajouté aux coefficients du spikegramme. Dans le cas de l’attaque de remplacement parcimonieuse, dans chaque segment du signal, les caractéristiques spectro-temporelles du signal (les décharges temporelles ;‘time spikes’) se trouvent en utilisant le spikegramme et les spikes temporelles et similaires sont remplacés par une autre. Pour comparer l’efficacité des attaques proposées, nous les comparons au décodeur du tatouage à spectre étendu. Il est démontré que l’attaque par remplacement parcimonieux réduit la corrélation normalisée du décodeur de spectre étendu avec un plus grand facteur par rapport à la situation où le décodeur de spectre étendu est attaqué par la transformation MP3 (32 kbps) et 24 kbps USAC.Abstract : Every year global music piracy is making billion dollars of economic, job, workers’ earnings losses and also million dollars loss in tax revenues. Most of the music piracy is because of rapid growth and easiness of current technologies for copying, sharing, manipulating and distributing musical data [Domingo, 2015], [Siwek, 2007]. Audio watermarking has been proposed as one approach for copyright protection and tamper localization of audio signals to prevent music piracy. In this thesis, we use the spikegram- which is a bio-inspired sparse representation- to propose a novel approach to design an audio tamper localization method as well as an audio copyright protection method and also a new perceptual attack against any audio watermarking system. First, we propose a tampering localization method for audio signal, based on a Modified Spread Spectrum (MSS) approach. Perceptual Matching Pursuit (PMP) is used to compute the spikegram (which is a sparse and time-shift invariant representation of audio signals) as well as 2-D masking thresholds. Then, an authentication code (which includes an Identity Number, ID) is inserted inside the sparse coefficients. For high quality watermarking, the watermark data are multiplied with masking thresholds. The time domain watermarked signal is re-synthesized from the modified coefficients and the signal is sent to the decoder. To localize a tampered segment of the audio signal, at the decoder, the ID’s associated to intact segments are detected correctly, while the ID associated to a tampered segment is mis-detected or not detected. To achieve high capacity, we propose a modified version of the improved spread spectrum watermarking called MSS (Modified Spread Spectrum). We performed a mean opinion test to measure the quality of the proposed watermarking system. Also, the bit error rates for the presented tamper localization method are computed under several attacks. In comparison to conventional methods, the proposed tamper localization method has the smallest number of mis-detected tampered frames, when only one frame is tampered. In addition, the mean opinion test experiments confirms that the proposed method preserves the high quality of input audio signals. Moreover, we introduce a new audio watermarking technique based on a kernel-based representation of audio signals. A perceptive sparse representation (spikegram) is combined with a dictionary of gammatone kernels to construct a robust representation of sounds. Compared to traditional phase embedding methods where the phase of signal’s Fourier coefficients are modified, in this method, the watermark bit stream is inserted by modifying the phase of gammatone kernels. Moreover, the watermark is automatically embedded only into kernels with high amplitudes where all masked (non-meaningful) gammatones have been already removed. Two embedding methods are proposed, one based on the watermark embedding into the sign of gammatones (one dictionary method) and another one based on watermark embedding into both sign and phase of gammatone kernels (two-dictionary method). The robustness of the proposed method is shown against 32 kbps MP3 with an embedding rate of 56.5 bps while the state of the art payload for 32 kbps MP3 robust iii iv watermarking is lower than 50.3 bps. Also, we showed that the proposed method is robust against unified speech and audio codec (24 kbps USAC, Linear predictive and Fourier domain modes) with an average payload of 5 − 15 bps. Moreover, it is shown that the proposed method is robust against a variety of signal processing transforms while preserving quality. Finally, three perceptual attacks are proposed in the perceptual sparse domain using spikegram. These attacks are called PMP, inaudible noise adding and the sparse replacement attacks. In PMP attack, the host signals are represented and re-synthesized with spikegram. In inaudible noise attack, the inaudible noise is generated and added to the spikegram coefficients. In sparse replacement attack, each specific frame of the spikegram representation - when possible - is replaced with a combination of similar frames located in other parts of the spikegram. It is shown than the PMP and inaudible noise attacks have roughly the same efficiency as the 32 kbps MP3 attack, while the replacement attack reduces the normalized correlation of the spread spectrum decoder with a greater factor than when attacking with 32 kbps MP3 or 24 kbps unified speech and audio coding (USAC)

Journal of Telecommunications and Information Technology, 2014, nr 2

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Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest