449 research outputs found

    Detection and Isolation of Faults and Cyberattacks in Nonlinear Cyber-Physical Systems using Neural Networks

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    The theory of Cyber-physical systems (CPSs) has applications in critical infrastructures such as smart grids, manufacturing systems, transportation systems, and autonomous systems such as Unmanned Aerial Vehicles(UAVs). In the CPS, there is a coordination between communication, computation, and control. The communication link in CPS can be subjected to malicious cyberattacks. On the other hand, the physical system in CPS can be faced with different faults such as sensor, actuator, and component faults. Therefore, two significant and challenging problems in CPS can be the detection of faults and cyberattacks. These two threats are intrinsically distinctive and need different strategies to deal with when they occur. This research mainly focuses on providing a methodology to detect and isolate faults and cyberattacks. This work considers false data injection and replay attacks as security threats. Two different adaptive neural network-based detection methods are proposed in this thesis. These adaptive neural networks are able to detect, isolate, and estimate false data injection, and replay attacks. Another contribution of this thesis is to provide a scheme for isolating faults and cyberattacks (false data injection and replay attacks) by using virtual sensors on the plant side, which makes the simultaneous detection of faults and false data injection cyberattacks possible. A nonlinear model of a quadrotor is considered the case study, and the performance of the neural network-based schemes is evaluated through various numerical simulation scenarios

    State of the art, challenges and prospects of wide-area event identification on transmission systems

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    The proliferation of advanced metering devices such as phasor measurement units (PMUs) along with communication systems readiness has opened new horizons for centralized protection and control of transmission systems. Wide-area event identification (WAEI) is considered an indispensable enabling block to these advanced applications. This paper is aimed at scrutinizing existing WAEI methods and discussing their prospects and shortcomings in improving the situational awareness of complex transmission systems. The disturbances of interest are those that significantly impact system operation and stability, namely short-circuit faults, line outages, and generation outages. The reluctance of system operators to entrust WAEI methods is discussed and linked to the inability of existing methods to deal with real-world challenges such as communication latencies, temporarily incomplete network observability, and the loss of the time synchronization signal. The superimposed-circuit concept is detailed and promoted as a powerful methodology with great unleashed potential for addressing these problems. The paper ends with remarks on the remaining research gaps that need to be addressed to fulfill the needs of power system operators, thus facilitating the uptake of WAEI methods in practice

    Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems

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    Intelligent transportation systems (ITSs) have been fueled by the rapid development of communication technologies, sensor technologies, and the Internet of Things (IoT). Nonetheless, due to the dynamic characteristics of the vehicle networks, it is rather challenging to make timely and accurate decisions of vehicle behaviors. Moreover, in the presence of mobile wireless communications, the privacy and security of vehicle information are at constant risk. In this context, a new paradigm is urgently needed for various applications in dynamic vehicle environments. As a distributed machine learning technology, federated learning (FL) has received extensive attention due to its outstanding privacy protection properties and easy scalability. We conduct a comprehensive survey of the latest developments in FL for ITS. Specifically, we initially research the prevalent challenges in ITS and elucidate the motivations for applying FL from various perspectives. Subsequently, we review existing deployments of FL in ITS across various scenarios, and discuss specific potential issues in object recognition, traffic management, and service providing scenarios. Furthermore, we conduct a further analysis of the new challenges introduced by FL deployment and the inherent limitations that FL alone cannot fully address, including uneven data distribution, limited storage and computing power, and potential privacy and security concerns. We then examine the existing collaborative technologies that can help mitigate these challenges. Lastly, we discuss the open challenges that remain to be addressed in applying FL in ITS and propose several future research directions

    Open reWall: Survey-to-production workflow for building renovation

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    A reabilitação de espaços interiores, num contexto de personalização em série, requer uma mudança na forma como os sistemas construtivos são desenhados, construídos e reutilizados. Recorrendo a plataformas digitais para a participação os arquitetos, em colaboração com outros atores na indústria AEC, podem desenvolver e oferecer soluções personalizadas e desmontáveis a utilizadores genéricos. Esta investigação propõe o uso de sistemas de construção personalizada em série (CPS) para fornecer sistemas de divisórias desmontáveis fabricadas digitalmente usando metodologias do levantamento à produção ligadas a configuradores online, em que os utilizadores co-projetam soluções para a reabilitação de espaços interiores. A metodologia de investigação socorre-se de pesquisa e análise teórica para definir critérios e objetivos a serem explorados em resolução de problemas de projeto. A partir destas experiências são sintetizados princípios e uma metodologia para a conceção de sistemas CPS de sistemas de divisórias personalizáveis e desmontáveis para a reabilitação. A metodologia clarifica os papeis dos atores, passos, e arquitetura do sistema para implementar um sistema CPS do levantamento à produção. A investigação demonstra que a metodologia de levantamento proposta é utilizável por utilizadores especialistas e não-especialistas, com os últimos a apresentarem em média melhores resultados, e que estes levantamentos têm precisão suficiente para processos do desenho à produção. Também se demonstra que a metodologia do levantamento à produção, a gramática genérica, e os critérios são úteis para os arquitetos conceberem sistemas de divisórias desmontáveis e personalizáveis para sistemas CPS abertos.Building renovation of interior spaces, in the context of mass customization, requires a shift in how construction systems are designed, built, and reused. Leveraging digital frameworks for user participation, architects in collaboration with other stakeholders in the AEC industry may design anddeliver customized and disassemble-able solutions to generic end-users. The research proposes mass customization construction (MCC) systems can deliver cost-effective digitally fabricated and disassemble-able construction systems using survey-to-production workflows deployed in web configurators for end-users to co-design solutions in building renovation. The research methodology uses theoretical inquiry and analysis to define criteria and objectives to be explored in design problem solving. From these experiments generalizable principles and a lowkey workflow for the design of MCC systems of customizable and disassemble-able partition wall construction systems for open building renovation are synthetized. The workflow clarifies stakeholder roles, steps, and system architecture to implement an MCC system from survey to production. This investigation demonstrates the proposed survey workflow is usable by non-expert and expert instance-designers, with the former having on-average better results, and that these can survey spaces with sufficient precision for design-to-production workflows. It is also shown the survey-to-production workflow, the generic grammar, and criteria are useful for architects to design customizable and disassemble-able partition wall systems for open MCC systems

    Influence of Organic and Conventional Management Systems on Soil Microarthropods in Protected and Non-Protected Areas

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    Aim: The EU Biodiversity Strategy 2030 aims to increase land-protected areas at 30% and organic farming at 25% of agricultural lands. But which measure could be more effective in preserving soil biodiversity? The aim of the study is, therefore, to assess soil health of arable lands under organic and conventional managements in Non-protected (NPAorg) and Protected (PAcon) areas of Marche region (Italy) and compare the influence of the applied farming practices on soil microarthropods in two seasons, characterized by different intensities of soil management practices: spring (lower) and autumn (higher). Method: Soil health has been assessed through the Biological Quality of Soil index based on arthropods (QBS-ar). Novel approaches (QBS-ab and FAI indices) which consider microarthropods’ abundance in the index calculation, have been also applied. Density (ind/m2), Acari/Collembola ratio, % of Oribatid mites on total mites, biodiversity indices, correlations with chemical-physical parameters, and ordination analysis (nMDS) have been evaluated. Results: In both seasons, different communities have been found according to management and, particularly, PAcon sites showed significantly higher levels of biodiversity compared to NPAorg. However, in autumn, microarthropod communities present higher stability in NPAorg sites, showing an opposite trend and fewer fluctuations of the indices compared to PAcon. Conclusions: PA, even in conventional managed soils, seem to enhance soil biodiversity, while organic farming in NPA, confers a higher resilience to soil, making microarthropod communities more stable. Results showed that agricultural intensity reduction combined with the increased integration of agroecosystems in protected areas may represent an effective, and sustainable measure to preserve soil biodiversity and its ecological services

    Sparsity and Coordination Constraints on Stealth Data Injection Attacks

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    In this thesis, data injection attacks (DIAs) to smart grid within Bayesian framework is studied from two perspectives: centralized and decentralized systems. The fundamental limits of the data injection attacks are characterized by the information measures. Specifically, two metrics, mutual information and the Kullback-Leibler (KL) divergence, quantifies the disruption caused by the attacks and the corresponding stealthiness, respectively. From the perspective of centralized system, a unique attacker constructs the attacks that jointly minimize the mutual information acquired from the measurements about the state variables and the KL divergence between the distribution of measurements with and without attacks. One of the main contributions in the centralized attack construction is the sparsity constraints. Two scenarios where the attacks between different locations are independent and correlated are studied, respectively. In independent attacks, the challenge of the combinatorial character of identifying the support of the sparse attack vector is circumvented by obtaining the closed-form solution to single measurement attack problem followed by a greedy construction that leverages the insight distilled. In correlated attacks, the challenge is tackled by incorporating an additional measurement that yields sequential sensor selection problem. The sequential procedure allows the attacker to identify the additional sensor first and character the corresponding covariances between the additional measurement and the compromised measurements. Following the studies on sparse attacks, a novel metric that describes the vulnerability of the measurements on smart grids to data integrity attacks is proposed. The new metric, coined vulnerability index (VuIx), leverages information theoretic measures to assess the attack effect on the fundamental limits of the disruption and detection tradeoff. The result of computing the VuIx of the measurements in the system yields an ordering of the measurements vulnerability based on the level of the exposure to data integrity attacks. The assessment on the measurements vulnerability of IEEE test systems observes that power injection measurements are overwhelmingly more vulnerable to data integrity attacks than power flow measurements. From the perspective of decentralized system, the attack constructions are determined by a group of attackers in a cooperative manner. The interaction between the attackers is formulated as a game with a normal form. The uniqueness of the Nash Equilibrium (NE) is characterized in different games where the attackers have different objectives. Closed-form expression for the best response of the attackers in different games are obtained and followed by best response dynamics that leads to the NEs. The sparsity constraint is considered in decentralized system where the attackers have limited access to sensors. The attack construction with sparsity constraints in decentralized system is also formulated as a game with a normal form. The uniqueness of the NE and the closed-form expression for the best response are obtained
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