Sensor Data Integrity Verification for Real-time and Resource Constrained Systems

Sensors are used in multiple applications that touch our lives and have become an integral part of modern life. They are used in building intelligent control systems in various industries like healthcare, transportation, consumer electronics, military, etc. Many mission-critical applications require sensor data to be secure and authentic. Sensor data security can be achieved using traditional solutions like cryptography and digital signatures, but these techniques are computationally intensive and cannot be easily applied to resource constrained systems. Low complexity data hiding techniques, on the contrary, are easy to implement and do not need substantial processing power or memory. In this applied research, we use and configure the established low complexity data hiding techniques from the multimedia forensics domain. These techniques are used to secure the sensor data transmissions in resource constrained and real-time environments such as an autonomous vehicle. We identify the areas in an autonomous vehicle that require sensor data integrity and propose suitable water-marking techniques to verify the integrity of the data and evaluate the performance of the proposed method against different attack vectors. In our proposed method, sensor data is embedded with application specific metadata and this process introduces some distortion. We analyze this embedding induced distortion and its impact on the overall sensor data quality to conclude that watermarking techniques, when properly configured, can solve sensor data integrity verification problems in an autonomous vehicle.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/167387/3/Raghavendar Changalvala Final Dissertation.pdfDescription of Raghavendar Changalvala Final Dissertation.pdf : Dissertatio

Authoritative and Unbiased Responses to Geographic Queries

Trust in information systems stem from two key properties of responses to queries regarding the state of the system, viz., i) authoritativeness, and ii) unbiasedness. That the response is authoritative implies that i) the provider (source) of the response, and ii) the chain of delegations through which the provider obtained the authority to respond, can be verified. The property of unbiasedness implies that no system data relevant to the query is deliberately or accidentally suppressed. The need for guaranteeing these two important properties stem from the impracticality for the verifier to exhaustively verify the correctness of every system process, and the integrity of the platform on which system processes are executed. For instance, the integrity of a process may be jeopardized by i) bugs (attacks) in computing hardware like Random Access Memory (RAM), input/output channels (I/O), and Central Processing Unit( CPU), ii) exploitable defects in an operating system, iii) logical bugs in program implementation, and iv) a wide range of other embedded malfunctions, among others. A first step in ensuing AU properties of geographic queries is the need to ensure AU responses to a specific type of geographic query, viz., point-location. The focus of this dissertation is on strategies to leverage assured point-location, for i) ensuring authoritativeness and unbiasedness (AU) of responses to a wide range of geographic queries; and ii) useful applications like Secure Queryable Dynamic Maps (SQDM) and trustworthy redistricting protocol. The specific strategies used for guaranteeing AU properties of geographic services include i) use of novel Merkle-hash tree- based data structures, and ii) blockchain networks to guarantee the integrity of the processes

A Framework for Facilitating Secure Design and Development of IoT Systems

The term Internet of Things (IoT) describes an ever-growing ecosystem of physical objects or things interconnected with each other and connected to the Internet. IoT devices consist of a wide range of highly heterogeneous inanimate and animate objects. Thus, a thing in the context of the IoT can even mean a person with blood pressure or heart rate monitor implant or a pet with a biochip transponder. IoT devices range from ordinary household appliances, such as smart light bulbs or smart coffee makers, to sophisticated tools for industrial automation. IoT is currently leading a revolutionary change in many industries and, as a result, a lot of industries and organizations are adopting the paradigm to gain a competitive edge. This allows them to boost operational efficiency and optimize system performance through real-time data management, which results in an optimized balance between energy usage and throughput. Another important application area is the Industrial Internet of Things (IIoT), which is the application of the IoT in industrial settings. This is also referred to as the Industrial Internet or Industry 4.0, where Cyber- Physical Systems (CPS) are interconnected using various technologies to achieve wireless control as well as advanced manufacturing and factory automation. IoT applications are becoming increasingly prevalent across many application domains, including smart healthcare, smart cities, smart grids, smart farming, and smart supply chain management. Similarly, IoT is currently transforming the way people live and work, and hence the demand for smart consumer products among people is also increasing steadily. Thus, many big industry giants, as well as startup companies, are competing to dominate the market with their new IoT products and services, and hence unlocking the business value of IoT. Despite its increasing popularity, potential benefits, and proven capabilities, IoT is still in its infancy and fraught with challenges. The technology is faced with many challenges, including connectivity issues, compatibility/interoperability between devices and systems, lack of standardization, management of the huge amounts of data, and lack of tools for forensic investigations. However, the state of insecurity and privacy concerns in the IoT are arguably among the key factors restraining the universal adoption of the technology. Consequently, many recent research studies reveal that there are security and privacy issues associated with the design and implementation of several IoT devices and Smart Applications (smart apps). This can be attributed, partly, to the fact that as some IoT device makers and smart apps development companies (especially the start-ups) reap business value from the huge IoT market, they tend to neglect the importance of security. As a result, many IoT devices and smart apps are created with security vulnerabilities, which have resulted in many IoT related security breaches in recent years. This thesis is focused on addressing the security and privacy challenges that were briefly highlighted in the previous paragraph. Given that the Internet is not a secure environ ment even for the traditional computer systems makes IoT systems even less secure due to the inherent constraints associated with many IoT devices. These constraints, which are mainly imposed by cost since many IoT edge devices are expected to be inexpensive and disposable, include limited energy resources, limited computational and storage capabilities, as well as lossy networks due to the much lower hardware performance compared to conventional computers. While there are many security and privacy issues in the IoT today, arguably a root cause of such issues is that many start-up IoT device manufacturers and smart apps development companies do not adhere to the concept of security by design. Consequently, some of these companies produce IoT devices and smart apps with security vulnerabilities. In recent years, attackers have exploited different security vulnerabilities in IoT infrastructures which have caused several data breaches and other security and privacy incidents involving IoT devices and smart apps. These have attracted significant attention from the research community in both academia and industry, resulting in a surge of proposals put forward by many researchers. Although research approaches and findings may vary across different research studies, the consensus is that a fundamental prerequisite for addressing IoT security and privacy challenges is to build security and privacy protection into IoT devices and smart apps from the very beginning. To this end, this thesis investigates how to bake security and privacy into IoT systems from the onset, and as its main objective, this thesis particularly focuses on providing a solution that can foster the design and development of secure IoT devices and smart apps, namely the IoT Hardware Platform Security Advisor (IoT-HarPSecA) framework. The security framework is expected to provide support to designers and developers in IoT start-up companies during the design and implementation of IoT systems. IoT-HarPSecA framework is also expected to facilitate the implementation of security in existing IoT systems. To accomplish the previously mentioned objective as well as to affirm the aforementioned assertion, the following step-by-step problem-solving approach is followed. The first step is an exhaustive survey of different aspects of IoT security and privacy, including security requirements in IoT architecture, security threats in IoT architecture, IoT application domains and their associated cyber assets, the complexity of IoT vulnerabilities, and some possible IoT security and privacy countermeasures; and the survey wraps up with a brief overview of IoT hardware development platforms. The next steps are the identification of many challenges and issues associated with the IoT, which narrowed down to the abovementioned fundamental security/privacy issue; followed by a study of different aspects of security implementation in the IoT. The remaining steps are the framework design thinking process, framework design and implementation, and finally, framework performance evaluation. IoT-HarPSecA offers three functionality features, namely security requirement elicitation security best practice guidelines for secure development, and above all, a feature that recommends specific Lightweight Cryptographic Algorithms (LWCAs) for both software and hardware implementations. Accordingly, IoT-HarPSecA is composed of three main components, namely Security Requirements Elicitation (SRE) component, Security Best Practice Guidelines (SBPG) component, and Lightweight Cryptographic Algorithms Recommendation (LWCAR) component, each of them servicing one of the aforementioned features. The author has implemented a command-line tool in C++ to serve as an interface between users and the security framework. This thesis presents a detailed description, design, and implementation of the SRE, SBPG, and LWCAR components of the security framework. It also presents real-world practical scenarios that show how IoT-HarPSecA can be used to elicit security requirements, generate security best practices, and recommend appropriate LWCAs based on user inputs. Furthermore, the thesis presents performance evaluation of the SRE, SBPG, and LWCAR components framework tools, which shows that IoT-HarPSecA can serve as a roadmap for secure IoT development.O termo Internet das coisas (IoT) é utilizado para descrever um ecossistema, em expansão, de objetos físicos ou elementos interconetados entre si e à Internet. Os dispositivos IoT consistem numa gama vasta e heterogénea de objetos animados ou inanimados e, neste contexto, podem pertencer à IoT um indivíduo com um implante que monitoriza a frequência cardíaca ou até mesmo um animal de estimação que tenha um biochip. Estes dispositivos variam entre eletrodomésticos, tais como máquinas de café ou lâmpadas inteligentes, a ferramentas sofisticadas de uso na automatização industrial. A IoT está a revolucionar e a provocar mudanças em várias indústrias e muitas adotam esta tecnologia para incrementar as suas vantagens competitivas. Este paradigma melhora a eficiência operacional e otimiza o desempenho de sistemas através da gestão de dados em tempo real, resultando num balanço otimizado entre o uso energético e a taxa de transferência. Outra área de aplicação é a IoT Industrial (IIoT) ou internet industrial ou Indústria 4.0, ou seja, uma aplicação de IoT no âmbito industrial, onde os sistemas ciberfísicos estão interconectados a diversas tecnologias de forma a obter um controlo de rede sem fios, bem como fabricações avançadas e automatização fabril. As aplicações da IoT estão a crescer e a tornarem-se predominantes em muitos domínios de aplicação inteligentes como sistemas de saúde, cidades, redes, agricultura e sistemas de fornecimento. Da mesma forma, a IoT está a transformar estilos de vida e de trabalho e assim, a procura por produtos inteligentes está constantemente a aumentar. As grandes indústrias e startups competem entre si de forma a dominar o mercado com os seus novos serviços e produtos IoT, desbloqueando o valor de negócio da IoT. Apesar da sua crescente popularidade, benefícios e capacidades comprovadas, a IoT está ainda a dar os seus primeiros passos e é confrontada com muitos desafios. Entre eles, problemas de conectividade, compatibilidade/interoperabilidade entre dispositivos e sistemas, falta de padronização, gestão das enormes quantidades de dados e ainda falta de ferramentas para investigações forenses. No entanto, preocupações quanto ao estado de segurança e privacidade ainda estão entre os fatores adversos à adesão universal desta tecnologia. Estudos recentes revelaram que existem questões de segurança e privacidade associadas ao design e implementação de vários dispositivos IoT e aplicações inteligentes (smart apps.), isto pode ser devido ao facto, em parte, de que alguns fabricantes e empresas de desenvolvimento de dispositivos (especialmente startups) IoT e smart apps., recolham o valor de negócio dos grandes mercados IoT, negligenciando assim a importância da segurança, resultando em dispositivos IoT e smart apps. com carências e violações de segurança da IoT nos últimos anos. Esta tese aborda os desafios de segurança e privacidade que foram supra mencionados. Visto que a Internet e os sistemas informáticos tradicionais são por vezes considerados inseguros, os sistemas IoT tornam-se ainda mais inseguros, devido a restrições inerentes a tais dispositivos. Estas restrições são impostas devido ao custo, uma vez que se espera que muitos dispositivos de ponta sejam de baixo custo e descartáveis, com recursos energéticos limitados, bem como limitações na capacidade de armazenamento e computacionais, e redes com perdas devido a um desempenho de hardware de qualidade inferior, quando comparados com computadores convencionais. Uma das raízes do problema é o facto de que muitos fabricantes, startups e empresas de desenvolvimento destes dispositivos e smart apps não adiram ao conceito de segurança por construção, ou seja, logo na conceção, não preveem a proteção da privacidade e segurança. Assim, alguns dos produtos e dispositivos produzidos apresentam vulnerabilidades na segurança. Nos últimos anos, hackers maliciosos têm explorado diferentes vulnerabilidades de segurança nas infraestruturas da IoT, causando violações de dados e outros incidentes de privacidade envolvendo dispositivos IoT e smart apps. Estes têm atraído uma atenção significativa por parte das comunidades académica e industrial, que culminaram num grande número de propostas apresentadas por investigadores científicos. Ainda que as abordagens de pesquisa e os resultados variem entre os diferentes estudos, há um consenso e pré-requisito fundamental para enfrentar os desafios de privacidade e segurança da IoT, que buscam construir proteção de segurança e privacidade em dispositivos IoT e smart apps. desde o fabrico. Para esta finalidade, esta tese investiga como produzir segurança e privacidade destes sistemas desde a produção, e como principal objetivo, concentra-se em fornecer soluções que possam promover a conceção e o desenvolvimento de dispositivos IoT e smart apps., nomeadamente um conjunto de ferramentas chamado Consultor de Segurança da Plataforma de Hardware da IoT (IoT-HarPSecA). Espera-se que o conjunto de ferramentas forneça apoio a designers e programadores em startups durante a conceção e implementação destes sistemas ou que facilite a integração de mecanismos de segurança nos sistemas préexistentes. De modo a alcançar o objetivo proposto, recorre-se à seguinte abordagem. A primeira fase consiste num levantamento exaustivo de diferentes aspetos da segurança e privacidade na IoT, incluindo requisitos de segurança na arquitetura da IoT e ameaças à sua segurança, os seus domínios de aplicação e os ativos cibernéticos associados, a complexidade das vulnerabilidades da IoT e ainda possíveis contramedidas relacionadas com a segurança e privacidade. Evolui-se para uma breve visão geral das plataformas de desenvolvimento de hardware da IoT. As fases seguintes consistem na identificação dos desafios e questões associadas à IoT, que foram restringidos às questões de segurança e privacidade. As demais etapas abordam o processo de pensamento de conceção (design thinking), design e implementação e, finalmente, a avaliação do desempenho. O IoT-HarPSecA é composto por três componentes principais: a Obtenção de Requisitos de Segurança (SRE), Orientações de Melhores Práticas de Segurança (SBPG) e a recomendação de Componentes de Algoritmos Criptográficos Leves (LWCAR) na implementação de software e hardware. O autor implementou uma ferramenta em linha de comandos usando linguagem C++ que serve como interface entre os utilizadores e a IoT-HarPSecA. Esta tese apresenta ainda uma descrição detalhada, desenho e implementação das componentes SRE, SBPG, e LWCAR. Apresenta ainda cenários práticos do mundo real que demostram como o IoT-HarPSecA pode ser utilizado para elicitar requisitos de segurança, gerar boas práticas de segurança (em termos de recomendações de implementação) e recomendar algoritmos criptográficos leves apropriados com base no contributo dos utilizadores. De igual forma, apresenta-se a avaliação do desempenho destes três componentes, demonstrando que o IoT-HarPSecA pode servir como um roteiro para o desenvolvimento seguro da IoT

Optimisation of Tamper Localisation and Recovery Watermarking Techniques

Digital watermarking has found many applications in many fields, such as: copyright tracking, media authentication, tamper localisation and recovery, hardware control, and data hiding. The idea of digital watermarking is to embed arbitrary data inside a multimedia cover without affecting the perceptibility of the multimedia cover itself. The main advantage of using digital watermarking over other techniques, such as signature based techniques, is that the watermark is embedded into the multimedia cover itself and will not be removed even with the format change. Image watermarking techniques are categorised according to their robustness against modification into: fragile, semi-fragile, and robust watermarking. In fragile watermarking any change to the image will affect the watermark, this makes fragile watermarking very useful in image authentication applications, as in medical and forensic fields, where any tampering of the image is: detected, localised, and possibly recovered. Fragile watermarking techniques are also characterised by a higher capacity when compared to semi-fragile and robust watermarking. Semifragile watermarking techniques resist some modifications, such as lossy compression and low pass filtering. Semi-fragile watermarking can be used in authentication and copyright validation applications whenever the amount of embedded information is small and the expected modifications are not severe. Robust watermarking techniques are supposed to withstand more severe modifications, such as rotation and geometrical bending. Robust watermarking is used in copyright validation applications, where copyright information in the image must remains accessible even after severe modification. This research focuses on the application of image watermarking in tamper localisation and recovery and it aims to provide optimisation for some of its aspects. The optimisation aims to produce watermarking techniques that enhance one or more of the following aspects: consuming less payload, having better recovery quality, recovering larger tampered area, requiring less calculations, and being robust against the different counterfeiting attacks. Through the survey of the main existing techniques, it was found that most of them are using two separate sets of data for the localisation and the recovery of the tampered area, which is considered as a redundancy. The main focus in this research is to investigate employing image filtering techniques in order to use only one set of data for both purposes, leading to a reduced redundancy in the watermark embedding and enhanced capacity. Four tamper localisation and recovery techniques were proposed, three of them use one set of data for localisation and recovery while the fourth one is designed to be optimised and gives a better performance even though it uses separate sets of data for localisation and recovery. The four techniques were analysed and compared to two recent techniques in the literature. The performance of the proposed techniques vary from one technique to another. The fourth technique shows the best results regarding recovery quality and Probability of False Acceptance (PFA) when compared to the other proposed techniques and the two techniques in the literature, also, all proposed techniques show better recovery quality when compared to the two techniques in the literature

Erasable PUFs: Formal treatment and generic design

Physical Unclonable Functions (PUFs) have not only been suggested as new key storage mechanism, but - in the form of so-called "Strong PUFs"- also as cryptographic primitives in advanced schemes, including key exchange, oblivious transfer, or secure multi-party computation. This notably extends their application spectrum, and has led to a sequence of publications at leading venues such as IEEE S&P, CRYPTO, and EUROCRYPT in the past[3,6,10,11,29, 41]. However, one important unresolved problem is that adversaries can break the security of all these advanced protocols if they gain physical access to the employed Strong PUFs after protocol completion [41]. It has been formally proven[49] that this issue cannot be overcome by techniques on the protocol side alone, but requires resolution on the hardware level - the only fully effective known countermeasure being so-called Erasable PUFs. Building on this work, this paper is the first to describe a generic method how any given silicon Strong PUF with digital CRP-interface can be turned into an Erasable PUFs[36]. We describe how the Strong PUF can be surrounded with a trusted control logic that allows the blocking (or "erasure") of single CRPs. We implement our approach, which we call "GeniePUF", on FPGA, reporting detailed performance data and practicality figures. Furthermore, we develop the first comprehensive definitional framework for Erasable PUFs. Our work so re-establishes the effective usability of Strong PUFs in advanced cryptographic applications, and in the realistic case adversaries get access to the Strong PUF after protocol completion

Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Copyright protection of scalar and multimedia sensor network data using digital watermarking

This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN

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)