Cooperative Data Backup for Mobile Devices

Les dispositifs informatiques mobiles tels que les ordinateurs portables, assistants personnels et téléphones portables sont de plus en plus utilisés. Cependant, bien qu'ils soient utilisés dans des contextes où ils sont sujets à des endommagements, à la perte, voire au vol, peu de mécanismes permettent d'éviter la perte des données qui y sont stockées. Dans cette thèse, nous proposons un service de sauvegarde de données coopératif pour répondre à ce problème. Cette approche tire parti de communications spontanées entre de tels dispositifs, chaque dispositif stockant une partie des données des dispositifs rencontrés. Une étude analytique des gains de cette approche en termes de sûreté de fonctionnement est proposée. Nous étudions également des mécanismes de stockage réparti adaptés. Les problèmes de coopération entre individus mutuellement suspicieux sont également abordés. Enfin, nous décrivons notre mise en oeuvre du service de sauvegarde coopérative. ABSTRACT : Mobile devices such as laptops, PDAs and cell phones are increasingly relied on but are used in contexts that put them at risk of physical damage, loss or theft. However, few mechanisms are available to reduce the risk of losing the data stored on these devices. In this dissertation, we try to address this concern by designing a cooperative backup service for mobile devices. The service leverages encounters and spontaneous interactions among participating devices, such that each device stores data on behalf of other devices. We first provide an analytical evaluation of the dependability gains of the proposed service. Distributed storage mechanisms are explored and evaluated. Security concerns arising from thecooperation among mutually suspicious principals are identified, and core mechanisms are proposed to allow them to be addressed. Finally, we present our prototype implementation of the cooperative backup servic

Dynamic Switching State Systems for Visual Tracking

This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together

Dynamic Switching State Systems for Visual Tracking

This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together

PIS: IoT & Industry 4.0 Challenges

International audienceIn the era of Industry 4.0, digital manufacturing is evolving into smart manufacturing. This evolution impacts companies in three main areas: organization, people, and technologies. This chapter analyzes the Internet of Things (IoT) and Cyber-Physical Systems (CPS)—key technologies transforming the physical world into a digitalized physical world. IoT and CPS provide factories with sensing capabilities, perform data and context capture and allow them to act/react to optimize the value chain. We survey the recent state-of-the-art development of the Industrial Internet of Things (IIoT)—also known as IoT and CPS in the context of Industry 4.0, from a protocol, architecture, and standard point-of-view. We also explore key challenges and future research directions for extensive industrial adoption of these technologies

Automação de edifícios com tolerância a falhas

Mestrado em Engenharia de Computadores e TelemáticaEsta dissertação enquadra-se no projecto SmartLighting e tem como objectivo criar uma solução energeticamente eficiente para edifícios e espaços inteligentes. Numa primeira fase, esta dissertação apresenta uma revisão das soluções existentes de automação de edifícios e, posteriormente, propõe uma solução baseada em princípios da Internet das Coisas e sistemas de processamento complexo de eventos, capaz de criar um ambiente inteligente, autónomo e resiliente a falhas. O foco do trabalho está na criação de um software leve para ser colocado em dispositivos com pouca capacidade de processamento de modo a poderem, não só ser um meio para comunicação com dispositivos inteligentes, mas também habilitados para oferecer capacidades de processamento de eventos em casos de emergência.This dissertation was was done within the scope of the SmartLighting project and aims to create an energy efficient solution for buildings and smart spaces. In a first phase, this dissertation presents a review of existing building automation solutions and later proposes a solution based on Internet of Things (IoT) principles and Complex Event Processing (CEP) systems, capable of creating a smart, autonomous and fail resilient environment. The focus of the work is on creating a lightweight software to be placed on devices with low processing capacity so that they can not only be a means of communicating with intelligent devices but also enabled to provide event processing capabilities in cases of emergency

Deep Gaussian Processes: Advances in Models and Inference

Hierarchical models are certainly in fashion these days. It seems difficult to navigate the field of machine learning without encountering `deep' models of one sort or another. The popularity of the deep learning revolution has been driven by some striking empirical successes, prompting both intense rapture and intense criticism. The criticisms often centre around the lack of model uncertainty, leading to sometimes drastically overconfident predictions. Others point to the lack of a mechanism for incorporating prior knowledge, and the reliance on large datasets. A widely held hope is that a Bayesian approach might overcome these problems. The deep Gaussian process presents a paradigm for building deep models from a Bayesian perspective. A Gaussian process is a prior for functions. A deep Gaussian process uses several Gaussian process functions and combines them hierarchically through composition (that is, the output of one is the input to the next). The deep Gaussian process promises to capture the compositional nature of deep learning while mitigating some of the disadvantages through a Bayesian approach. The thesis develops deep Gaussian process modelling in a number of ways. The model is first interpreted differently from previous work, not as a `hierarchical prior' but as a factorized prior with an hierarchical likelihood. Mean functions are suggested to avoid issues of degeneracy and to aid initialization. The main contribution is a new method of inference that avoids the burden of representing the function values directly through an application of sparse variational inference. This method scales to arbitrarily large data and is shown to work well in practice through experiments. The use of variational inference recasts (approximate) inference as optimization of Gaussian distributions. This optimization has an exploitable geometry via the natural gradient. The natural gradient is shown to be advantageous for single layer non-conjugate models, and for the (final layer of a) deep Gaussian process model. Deep Gaussian processes can be a model both for complex associations between variables and complex marginal distributions of single variables. Incorporating noise in the hierarchy leads to complex marginal distribution through the non-linearities of the mappings at each layer. The inference required for noisy variables cannot be handled with sparse methods, as sparse methods rely on correlations between variables, which are absent for noisy variables. Instead, a more direct approach is developed, using an importance weighted variational scheme.Open Acces

The "Particular Situation" in the Futa Jallon: Ethnicity, Region, and Nation in Twentieth-Century Guinea

The dissertation begins with a seeming paradox in twentieth-century Guinean history: how did ethnic Fulbe, constituting some 40% of Guinea’s population, come to be labeled “neo-colonial traitors” in a country that was supposedly founded upon a broad-based, multi-ethnic nationalism? Less than two decades after Guineans’ 1958 rejection of membership in a reformed French community, Guinea’s first president, Sékou Touré, argued that there existed a “particular situation” in the Futa Jallon, the historic homeland of the Fulbe, that had caused the Fulbe to diverge from the rest of the country. Using Touré’s speech announcing the “particular situation” as a point of entry, the dissertation argues that the legacy of hierarchies rooted in the pre-colonial Islamic Futa Jallon state, contestation between African political parties during decolonization, and the partial failure of the post-colonial state’s attempt to create a “modern” Guinean society combined to produce a Fulbe fragment of the Guinean nation. The dissertation’s first two chapters examine how the presentation and practice of chiefly authority in the Futa Jallon following the imposition of French rule resulted from the entanglement of local and colonial discourses, and how the opening of colonial spaces – markets, cities, and cash crop fields, for example – allowed room for marginalized groups such as former slaves and women to renegotiate Fulbe social hierarchies. The dissertation then examines how the practical work of building political coalitions as well as ideological debates about the meaning of modernity during decolonization led to the marginalization of Fulbe elites and the conceptual “othering” of the Fulbe. The dissertation then shifts to Fulbe (self-)positioning within an emerging post-colonial order. One chapter argues that political, economic, and social reforms enacted by the Touré-led government marked the Fulbe as resistant to attempts at modernization, leading to the elimination of Fulbe elites and the designation of the Fulbe as “anti-citizens.” Another follows the pathways of Fulbe exiles, migrants, and merchants took after independence, arguing that the Fulbe diaspora created by repression shaped ideas about citizenship, political community, and belonging in post-colonial Guinea. The histories examined by the dissertation demonstrate that the current welding of political community and ethnicity is the result of Guinea’s status as a post-slavery, post-colonial, and post-socialist society, rather than the deterministic result of “natural” regional differences or the structure of the colonial state. The dissertation is based upon two years of research in Guinea, Senegal, and France. Using previously neglected oral and archival sources in French and Pular, it makes several significant interventions in Africanist historiography. Countering temporal and conceptual frameworks based solely upon colonial intervention, I argue that ideas about ethnicity were formed and reformed throughout the twentieth century and that ethnic identities were shaped as much by local ideas as they were by the colonial state. I also argue that, contradicting portrayals of post-colonial balkanization, debates about the nation and citizenship after independence took place in both local and trans-national contexts. Lastly, while previous studies have often cast ethnicity and nationalism in Africa as inherently different forms of political thought, I argue that both arise from similar processes. The failure of the post-colonial African nation-state is often attributed to the supposed immutability of ethnic identity. The political history of Guinea, on the other hand, demonstrates that African politicians and parties used ethnicities as an “other” in opposition to which they articulated their own visions of the nation. Thus, Fulbe identification and Guinean nationalism were in fact mutually formed and their histories closely intertwined over the course of the twentieth century

Electromagnetic Side-Channel Resilience against Lightweight Cryptography

Side-channel attacks are an unpredictable risk factor in cryptography. Therefore, observations of leakages through physical parameters, i.e., power and electromagnetic (EM) radiation, etc., of digital devices are essential to minimise vulnerabilities associated with cryptographic functions. Compared to costs in the past, performing side-channel attacks using inexpensive test equipment is becoming a reality. Internet-of-Things (IoT) devices are resource-constrained, and lightweight cryptography is a novel approach in progress towards IoT security. Thus, it would provide sufficient data and privacy protection in such a constrained ecosystem. Therefore, cryptanalysis of physical leakages regarding these emerging ciphers is crucial. EM side-channel attacks seem to cause a significant impact on digital forensics nowadays. Within existing literature, power analysis seems to have considerable attention in research whereas other phenomena, such as EM, should continue to be appropriately evaluated in playing a role in forensic analysis.The emphasis of this thesis is on lightweight cryptanalysis. The preliminary investigations showed no Correlation EManalysis (CEMA) of PRESENT lightweight algorithm. The PRESENT is a block cipher that promises to be adequate for IoT devices, and is expected to be used commercially in the future. In an effort to fill in this research gap, this work examines the capabilities of a correlation EM side-channel attack against the PRESENT. For that, Substitution box (S-box) of the PRESENT was targeted for its 1st round with the use of a minimum number of EM waveforms compared to other work in literature, which was 256. The attack indicates the possibility of retrieving 8 bytes of the secret key out of 10 bytes. The experimental process started from a Simple EMA (SEMA) and gradually enhanced up to a CEMA. The thesis presents the methodology of the attack modelling and the observations followed by a critical analysis. Also, a technical review of the IoT technology and a comprehensive literature review on lightweight cryptology are included