State estimation problem for power systems has long been a fundamental issue that demands a variety of methodologies dependent on the system settings. With recent introduction of advanced devices of phasor measurement units (PMUs) and dedicated communication networks, the infrastructure of power grids has been greatly improved. Coupled with the infrastructure improvements are three emerging issues for the state estimation problems, namely, the coexistence of both traditional and PMU measurements, the incomplete information resulting from delayed, missing and quantized measurements due to communication constraints, and the cyber-attacks on the communication channels. Three challenging problems are faced when dealing with the three issues in the state estimation program of power grids: 1) how to include the PMU measurements in the state estimator design, 2) how to account for the phenomena of incomplete information occurring in the measurements and design effective state estimators resilient to such phenomena, and 3) how to identify the system vulnerability in state estimation scheme and protect the estimation system against cyber-attacks. In this thesis, with the aim to solve the above problems, we develop several state estimation algorithms which tackle the issues of mixed measurements and incomplete information, and examine the cyber-security of the dynamic state estimation scheme. • To improve the estimation performance of power grids including PMU measurements, a hybrid extended Kalman filter and particle swarm optimization algorithm is developed, which has the advantages of being scalable to the numbers of the installed PMUs and being compatible with existing dynamic state estimation software as well. • Two kinds of network-induced phenomena, which leads to incomplete information of measurements, are considered. Specifically, the phenomenon of missing measurements is assumed to occur randomly and the missing probability is governed by a random variable, and the quantized nonlinear measurement model of power systems is presented where the quantization is assumed to be of logarithmic type. Then, the impact of the incomplete information on the overall estimation performance is taken into account when designing the estimator. Specifically, a modified extended Kalman filter is developed which is insensitive to the missing measurements in terms of acceptable probability, and a recursive filter is designed for the system with quantized measurements such that an upper bound of the estimation error is guaranteed and also minimized by appropriately designing the filter gain. • With the aim to reduce or eliminate the occurrence of the above-mentioned network-induced phenomena, we propose an event-based state estimation scheme with which communication transmission from the meters to the control centre can be greatly reduced. To ensure the estimation performance, we design the estimator gains by solving constrained optimization problems such that the estimation error covariances are guaranteed to be always less than a finite upper bound. • We examine the cyber-security of the dynamic state estimation system in power grids where the adversary is able to inject false data into the communication channels between PMUs and the control centre. The condition under which the attacks cause unbounded estimation errors is found. Furthermore, for system that is vulnerable to cyber-attacks, we propose a system protection scheme through which only a few (rather than all) communication channels require protection against false data injection attacks.

Le secteur du bâtiment, responsable de plus de 40% de consommation d’énergie globale et un tiers des émissions de gaz à effet de serre mondial, est un des centres de préoccupations autour des sujets liés au changement climatique et l’indépendance énergétique. Le travail de recherche a exigé l’apport de connaissances supplémentaires et la création d’outils spécifiques orientés sur l’optimisation globale du management énergétique des bâtiments de type tertiaire. Une problématique industrielle est associée à ces enjeux de transitions énergétique et écologique, à savoir le frein observé à la mise en place de plans d’actions de rénovation. En effet, pour des opérations d’optimisation ou de rénovation de petites-moyennes envergures, les coûts initiaux d’études et de métrologie représentent plus de 50% de leur coût global. Cette mise de fonds induit un retour sur investissement très long. Face à ce paramètre financier prohibitif, beaucoup d’entreprises sont réticentes à mettre en place ce type d’action. L’objectif opérationnel a donc été de proposer une solution permettant de réduire drastiquement ces coûts préliminaires.Les aspects abordés dans la thèse sont : l’état de l’art du fonctionnement du bâtiment et des enjeux associés, la création d’un outil de collecte et de remontée des données de fonctionnement et de performance du bâtiment grâce à un réseau de mesure in-situ dédié, concomitant à l’élaboration d’un modèle thermique simplifié adjoint facilitant la compréhension de son comportement, puis l’identification de ses paramètres "observables" de conception et de fonctionnement par méthode inverse, et enfin le calcul de sa consommation énergétique optimale grâce à une méthode d’optimisation. Plus spécifiquement, l’approche sera orientée vers le développement d’outils pour promouvoir un accès facilité à la réduction des consommations unitaires auprès des entreprises au niveau national et l’intégration d’une intelligence pour l’optimisation énergétique des éléments climatiques du bâtiment ou son usage, ou encore une interface ergonomique homme-machine permettant un management efficace de son fonctionnement. Dans les faits, le problème observé est holistique et ne peut pas être pris en compte de manière sectorielle. Il est impératif d’y intégrer tous les processus impliqués dans le bâtiment et son usage (aspect comportemental des usagers). L’approche utilisée a été orientée afin de prendre en compte ultérieurement des paramètres autres que strictement énergétique, tel que les coûts ou le confort / The building field is responsible of about 40% of global energy consumption and a third of world greenhouse gas emissions. It is a main concern subject in climate change issues and fossil fuel independency. The aim of the PhD work is to bring more knowledge about thermal modeling and to create specific tools which are capable of globally optimize the office building energy management. The industrial purpose is associated with its area of expertise, which is advice in energy and ecologic transition. It concerns the difficulty to implement a retrofit action planning. Indeed, for small or middle retrofit actions, the initial study and metrology costs represent over 50% of the overall cost. This down payment induces a long return of investment. Faced with this prohibitive financial parameter, a lot of companies are reluctant to implement this type of actions. The proposed purpose is a solution that drastically reduces preliminary costs. The aspects addressed in this thesis are: the building operation state of art and its associated issues, the creation of reporting and collecting data tool of building operation and performance thanks to a dedicated in-situ measurement network, concomitant with the development of a simplified adjoin thermal model. It facilitates the understanding of its behavior. Then the final aspect are the two steps of optimization. The first is the observable building design and operation parameters with an inverse method, the second is the calculation of optimal energy consumptions. The approach is specifically oriented through the development of tools allowing a facilitated access to energy reduction action for national companies. This should assist the integration of an intelligence for energy optimization for building climatics and thermal equipments or usage. The result could be a new ergonomic man-machine interface for stock building effective management. In the facts, the problem is holistic and cannot be handle sectorally. It is imperative to integrate all the process involved in the building and its use (user behavior). The approach have been oriented to take later into account other parameters than strictly energy, as costs of comfort

The security and integrity of TLS certificates are essential for ensuring secure transmission over the internet and protecting millions of people from man-in-the-middle attacks. Certificate Authorities (CA) play a crucial role in issuing and managing thesecertificates. This bachelor thesis presents a longitudinal analysis of certificate chains forpopular domains, examining their evolution over time and across different categories. Using publicly available certificate data from sources such as crt.sh and censys.io, we createda longitudinal dataset of certificate chains for domains from the Top 1-M list of Tranco.We categorized the certificates based on their type, and the particular service categories.We analyzed a selected set of domains over time and identified the patterns and trendsthat emerged in their certificate chains. Our analysis revealed several noteworthy trends,including an increase in the use of new CAs and a shift of which types of certificates areused, we also found a trend in shorter certificate chains and fewer paths from domain toroot certificate. This implies a more streamlined and simplified certificate process overtime until today. Our findings have implications for the broader cybersecurity communityand demonstrate the importance of ongoing monitoring and analysis of certificate chainsfor popular domains.

This thesis deals with predicting the latency between two network nodes, such as the two stations, two servers or server and station. The main reason for adoption of effective latency prediction techniques is the elimination of network load caused by unnecessary repeated transmissios or by direct measurement of the latency. Of the many proposed methods of latency estimation, this thesis is focused on methods using artificial coordinate systems with primary focus on the Vivaldi algorithm. Characteristics of the latency prediction methods and properties of various coordinate systems used in practice are evaluated. The issue of the number of dimensions of space defined only by the latency matrix between nodes is also mentioned. Furthermore, some other systems, based on logical clustering of nearby nodes, are mentioned. Description of simulation software VivaldiMonitor developed as part of the thesis is included. The primary purpose is analysis of the behavior of overlay networks implementing Vivaldi algorithm with less than a few hundred nodes. The Vivaldi algorithm is assessed by several simulations carried out using the aforementioned software.

La dynamique des Matières en Suspension (MES) dans les estuaires macrotidaux est fortement variable à la fois spatialement (du compartiment fluvial à l'embouchure de l'estuaire) et temporellement (de la seconde à plusieurs années), mais reste primordiale pour comprendre et quantifier la dynamique sédimentaire des environnements estuariens. Avec le développement croissant des réseaux de mesures haute-fréquence à l'échelle internationale, l'objectif principal de cette étude est de qualifier et de valoriser les mesures de turbidité acquises par un réseau de mesures haute fréquence (réseau SYNAPSES) implanté d'amont en aval sur l'estuaire de la Seine (France) à la fois (i) en matière de suivi de la dynamique des MES du compartiment fluvial au bouchon vaseux et (ii) en matière d'estimation des flux de MES sur différentes échelles spatio-temporelles de l'estuaire de la Seine. Les données acquises à partir du réseau SYNAPSES et des campagnes in situ (81 journées de 12 h - OBS-3+/YSI/LISST 100X-C/ADCP 600 kHz) sur quatre stations réparties de l'estuaire fluvial à la zone du bouchon vaseux, constituent un set de données extrêmement riche et unique sur les domaines estuariens. La variabilité des relations, établies entre les mesures de turbidité [NTU] et les mesures de concentrations en MES [g.L-1] sur chacune des campagnes de l'échelle tidale à annuelle, met en évidence l'effet (i) de la technologie interne du capteur et (ii) de la variabilité des propriétés optiques inhérentes des particules (diamètre médian D50), densité sèche rhô et efficacité de diffusion Qc) sur la sensibilité des différents capteurs optiques. L'analyse conjointe des données in situ et des données SYNAPSES a permis de calibrer les mesures de turbidité en concentration massique, avec une relation validée sur le cycle annuel, spécifique à chacune des stations et des incertitudes minimisées. Après une étude de la représentativité des stations du réseau vis-à-vis de la section, les flux instantanés de MES sont estimés (i) à partir des données de concentrations en MES et de débits acquis par l'ADCP sur l'intégralité de la section et (ii) à partir des concentrations ponctuelles en MES du réseau SYNAPSES couplées au modèle hydrodynamique MARS-3D. Les comparaisons des flux de MES in situ par rapport à ceux estimés par la combinaison SYNAPSES/MARS-3D permettent de proposer un coefficient spécifique à chacune des stations du réseau SYNAPSES, dans le but d'ajuster les flux instantanés de MES estimés, avec leurs incertitudes, à partir du réseau SYNAPSES à la réalité in situ. Les outils et les démarches développés dans la thèse sur l'estuaire de la Seine pauvent être appliqués à d'autres estuaires macrotidaux pour estimer les flux sédimentaires. / The dynamics of Suspended Particulate Matter (SPM) in macrotidal estuaries is highly variable both spatially (from the fluvial compartment to the estuary mouth) and temporally (from the second to several years), but it is essential to understand and quantify the sedimentary dynamics of estuarine environments. With the development of high-frequency measurement networks around the world, the main objective of this study is to qualify the turbidity measurements acquired by a high-frequency measurement network (SYNAPSES network) located on the Seine estuary (i) in terms of monitoring the SPM dynamics from the fluvial compartment to the turbidity maximal zone (TMZ) and (ii) in terms of estimation of the SPM fluxes on different spatio-temporal scales of the Seine estuary. Data acquired from the SYNAPSES network and complementary in situ campaigns (81 days of 12 h - OBS-3+/YSI/LISST 100X-C / ADCP 600 kHz) on four stations from the fluvial estuary of the Seine Estuary to the turbidity maximal zone, are an extremely rich and unique dataset on estuarine environments. The variability in the relationship between turbidity measurements [NTU] and SPM concentration measurements [g.L-1] on each campaign, reveals the effect of (i) the internal sensor technology and (ii) the variability of the particle inherent optical properties (median diameter D50, dry density rho and scattering efficiency Qc) on the sensitivity of different optical sensors. The analysis of the in situ and the SYNAPSES data allowed to calibrate the turbidity measurements in mass concentration, with a validated relationship on the annual cycle, specific to each of the stations and reduced uncertainties. After a study of the SYNAPSES station representativeness across the section, the instantaneous fluxes of SPM are estimated (i) from the SPM concentration and liquid flow data acquired by the ADCP on the global section and (ii) from the SPM concentrations of the SYNAPSES network coupled to the hydrodynamic model MARS-3D (estimation of the liquid flow). Comparisons of SPM fluxes in situ to those estimated by the combination SYNAPSES/MARS-3D allow to propose a specific coefficient for each of the SYNAPSES network stations, xith the aim of adjusting the SPM instantaneous fluxes estimated from the SYNAPSES network to the in situ reality, with reasonable uncertainties. the tools and approaches developed in the PhD thesis on the Seine estuary can be applied to other macrotidal estuaries to estimate sedimentary fluxes.