42 research outputs found

    Security and Privacy for Modern Wireless Communication Systems

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    The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

    Security in Computer and Information Sciences

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    This open access book constitutes the thoroughly refereed proceedings of the Second International Symposium on Computer and Information Sciences, EuroCybersec 2021, held in Nice, France, in October 2021. The 9 papers presented together with 1 invited paper were carefully reviewed and selected from 21 submissions. The papers focus on topics of security of distributed interconnected systems, software systems, Internet of Things, health informatics systems, energy systems, digital cities, digital economy, mobile networks, and the underlying physical and network infrastructures. This is an open access book

    Robust and secure resource management for automotive cyber-physical systems

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    2022 Spring.Includes bibliographical references.Modern vehicles are examples of complex cyber-physical systems with tens to hundreds of interconnected Electronic Control Units (ECUs) that manage various vehicular subsystems. With the shift towards autonomous driving, emerging vehicles are being characterized by an increase in the number of hardware ECUs, greater complexity of applications (software), and more sophisticated in-vehicle networks. These advances have resulted in numerous challenges that impact the reliability, security, and real-time performance of these emerging automotive systems. Some of the challenges include coping with computation and communication uncertainties (e.g., jitter), developing robust control software, detecting cyber-attacks, ensuring data integrity, and enabling confidentiality during communication. However, solutions to overcome these challenges incur additional overhead, which can catastrophically delay the execution of real-time automotive tasks and message transfers. Hence, there is a need for a holistic approach to a system-level solution for resource management in automotive cyber-physical systems that enables robust and secure automotive system design while satisfying a diverse set of system-wide constraints. ECUs in vehicles today run a variety of automotive applications ranging from simple vehicle window control to highly complex Advanced Driver Assistance System (ADAS) applications. The aggressive attempts of automakers to make vehicles fully autonomous have increased the complexity and data rate requirements of applications and further led to the adoption of advanced artificial intelligence (AI) based techniques for improved perception and control. Additionally, modern vehicles are becoming increasingly connected with various external systems to realize more robust vehicle autonomy. These paradigm shifts have resulted in significant overheads in resource constrained ECUs and increased the complexity of the overall automotive system (including heterogeneous ECUs, network architectures, communication protocols, and applications), which has severe performance and safety implications on modern vehicles. The increased complexity of automotive systems introduces several computation and communication uncertainties in automotive subsystems that can cause delays in applications and messages, resulting in missed real-time deadlines. Missing deadlines for safety-critical automotive applications can be catastrophic, and this problem will be further aggravated in the case of future autonomous vehicles. Additionally, due to the harsh operating conditions (such as high temperatures, vibrations, and electromagnetic interference (EMI)) of automotive embedded systems, there is a significant risk to the integrity of the data that is exchanged between ECUs which can lead to faulty vehicle control. These challenges demand a more reliable design of automotive systems that is resilient to uncertainties and supports data integrity goals. Additionally, the increased connectivity of modern vehicles has made them highly vulnerable to various kinds of sophisticated security attacks. Hence, it is also vital to ensure the security of automotive systems, and it will become crucial as connected and autonomous vehicles become more ubiquitous. However, imposing security mechanisms on the resource constrained automotive systems can result in additional computation and communication overhead, potentially leading to further missed deadlines. Therefore, it is crucial to design techniques that incur very minimal overhead (lightweight) when trying to achieve the above-mentioned goals and ensure the real-time performance of the system. We address these issues by designing a holistic resource management framework called ROSETTA that enables robust and secure automotive cyber-physical system design while satisfying a diverse set of constraints related to reliability, security, real-time performance, and energy consumption. To achieve reliability goals, we have developed several techniques for reliability-aware scheduling and multi-level monitoring of signal integrity. To achieve security objectives, we have proposed a lightweight security framework that provides confidentiality and authenticity while meeting both security and real-time constraints. We have also introduced multiple deep learning based intrusion detection systems (IDS) to monitor and detect cyber-attacks in the in-vehicle network. Lastly, we have introduced novel techniques for jitter management and security management and deployed lightweight IDSs on resource constrained automotive ECUs while ensuring the real-time performance of the automotive systems

    Optimized and Automated Machine Learning Techniques Towards IoT Data Analytics and Cybersecurity

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    The Internet-of-Things (IoT) systems have emerged as a prevalent technology in our daily lives. With the wide spread of sensors and smart devices in recent years, the data generation volume and speed of IoT systems have increased dramatically. In most IoT systems, massive volumes of data must be processed, transformed, and analyzed on a frequent basis to enable various IoT services and functionalities. Machine Learning (ML) approaches have shown their capacity for IoT data analytics. However, applying ML models to IoT data analytics tasks still faces many difficulties and challenges. The first challenge is to process large amounts of dynamic IoT data to make accurate and informed decisions. The second challenge is to automate and optimize the data analytics process. The third challenge is to protect IoT devices and systems against various cyber threats and attacks. To address the IoT data analytics challenges, this thesis proposes various ML-based frameworks and data analytics approaches in several applications. Specifically, the first part of the thesis provides a comprehensive review of applying Automated Machine Learning (AutoML) techniques to IoT data analytics tasks. It discusses all procedures of the general ML pipeline. The second part of the thesis proposes several supervised ML-based novel Intrusion Detection Systems (IDSs) to improve the security of the Internet of Vehicles (IoV) systems and connected vehicles. Optimization techniques are used to obtain optimized ML models with high attack detection accuracy. The third part of the thesis developed unsupervised ML algorithms to identify network anomalies and malicious network entities (e.g., attacker IPs, compromised machines, and polluted files/content) to protect Content Delivery Networks (CDNs) from service targeting attacks, including distributed denial of service and cache pollution attacks. The proposed framework is evaluated on real-world CDN access log data to illustrate its effectiveness. The fourth part of the thesis proposes adaptive online learning algorithms for addressing concept drift issues (i.e., data distribution changes) and effectively handling dynamic IoT data streams in order to provide reliable IoT services. The development of drift adaptive learning methods can effectively adapt to data distribution changes and avoid data analytics model performance degradation

    Real-Time Trace Decoding and Monitoring for Safety and Security in Embedded Systems

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    Integrated circuits and systems can be found almost everywhere in today’s world. As their use increases, they need to be made safer and more perfor mant to meet current demands in processing power. FPGA integrated SoCs can provide the ideal trade-off between performance, adaptability, and energy usage. One of today’s vital challenges lies in updating existing fault tolerance techniques for these new systems while utilizing all available processing capa bilities, such as multi-core and heterogeneous processing units. Control-flow monitoring is one of the primary mechanisms described for error detection at the software architectural level for the highest grade of hazard level clas sifications (e.g., ASIL D) described in industry safety standards ISO-26262. Control-flow errors are also known to compose the majority of detected errors for ICs and embedded systems in safety-critical and risk-susceptible environ ments [5]. Software-based monitoring methods remain the most popular [6–8]. However, recent studies show that the overheads they impose make actual reliability gains negligible [9, 10]. This work proposes and demonstrates a new control flow checking method implemented in FPGA for multi-core embedded systems called control-flow trace checker (CFTC). CFTC uses existing trace and debug subsystems of modern processors to rebuild their execution states. It can iden tify any errors in real-time by comparing executed states to a set of permitted state transitions determined statically. This novel implementation weighs hardware resource trade-offs to target mul tiple independent tasks in multi-core embedded applications, as well as single core systems. The proposed system is entirely implemented in hardware and isolated from all monitored software components, requiring 2.4% of the target FPGA platform resources to protect an execution unit in its entirety. There fore, it avoids undesired overheads and maintains deterministic error detection latencies, which guarantees reliability improvements without impairing the target software system. Finally, CFTC is evaluated under different software i Resumo fault-injection scenarios, achieving detection rates of 100% of all control-flow errors to wrong destinations and 98% of all injected faults to program binaries. All detection times are further analyzed and precisely described by a model based on the monitor’s resources and speed and the software application’s control-flow structure and binary characteristics.Circuitos integrados estão presentes em quase todos sistemas complexos do mundo moderno. Conforme sua frequência de uso aumenta, eles precisam se tornar mais seguros e performantes para conseguir atender as novas demandas em potência de processamento. Sistemas em Chip integrados com FPGAs conseguem prover o balanço perfeito entre desempenho, adaptabilidade, e uso de energia. Um dos maiores desafios agora é a necessidade de atualizar técnicas de tolerância à falhas para estes novos sistemas, aproveitando os novos avanços em capacidade de processamento. Monitoramento de fluxo de controle é um dos principais mecanismos para a detecção de erros em nível de software para sistemas classificados como de alto risco (e.g. ASIL D), descrito em padrões de segurança como o ISO-26262. Estes erros são conhecidos por compor a maioria dos erros detectados em sistemas integrados [5]. Embora métodos de monitoramento baseados em software continuem sendo os mais populares [6–8], estudos recentes mostram que seus custos adicionais, em termos de performance e área, diminuem consideravelmente seus ganhos reais em confiabilidade [9, 10]. Propomos aqui um novo método de monitora mento de fluxo de controle implementado em FPGA para sistemas embarcados multi-core. Este método usa subsistemas de trace e execução de código para reconstruir o estado atual do processador, identificando erros através de com parações entre diferentes estados de execução da CPU. Propomos uma implementação que considera trade-offs no uso de recuros de sistema para monitorar múltiplas tarefas independetes. Nossa abordagem suporta o monitoramento de sistemas simples e também de sistemas multi-core multitarefa. Por fim, nossa técnica é totalmente implementada em hardware, evitando o uso de unidades de processamento de software que possa adicionar custos indesejáveis à aplicação em perda de confiabilidade. Propomos, assim, um mecanismo de verificação de fluxo de controle, escalável e extensível, para proteção de sistemas embarcados críticos e multi-core

    Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design – FMCAD 2021

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    The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system verification. FMCAD provides a leading forum to researchers in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system design including verification, specification, synthesis, and testing

    Holistic Control for Cyber-Physical Systems

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    The Industrial Internet of Things (IIoT) are transforming industries through emerging technologies such as wireless networks, edge computing, and machine learning. However, IIoT technologies are not ready for control systems for industrial automation that demands control performance of physical processes, resiliency to both cyber and physical disturbances, and energy efficiency. To meet the challenges of IIoT-driven control, we propose holistic control as a cyber-physical system (CPS) approach to next-generation industrial automation systems. In contrast to traditional industrial automation systems where computing, communication, and control are managed in isolation, holistic control orchestrates the management of cyber platforms (networks and computing platforms) and physical plant control at run-time in an integrated architecture. Specifically, this dissertation research comprises the following primary components. Holistic wireless control: The core of holistic wireless control is a holistic controller comprising a plant controller and a network controller cooperating with each other. At run-time the holistic controller generates (1) control commands to the physical plant and (2) network reconfiguration commands to wireless networks based on both physical and network states. This part of dissertation research focused on the design and evaluation of holistic controllers exploiting a range of network reconfiguration strategies: (1) adapting transmission redundancy, (2) adapting sampling rates, (3) self-triggered control, and (4) dynamic transmission scheduling. Furthermore, we develop novel network reconfiguration protocols (NRP) as actuators to control network configurations in holistic control. Holistic edge control: This part of dissertation research explores edge computing as a multitier computing platform for holistic control. The proposed switching multi-tier control (SMC) dynamically switches controllers located on different computation platforms, thereby exploiting the trade-off between computation and communication in a multi-tier computing platform. We also design the stability switch between local and edge controllers under information loss from another perspective, based on co-design of edge and local controllers that are designed via a joint Lyapunov function. Real-time wireless cyber-physical simulators: To evaluate holistic control, we extend the Wireless Cyber-Physical Simulator (WCPS) to integrate simulated physical plants (in Simulink) with real wireless networks (WCPS-RT) and edge computing platforms (WCPS-EC). The real-time WCPS provides a holistic environment for CPS simulations that incorporate wireless dynamics that are challenging to simulate accurately, explore the impacts and trade-off of computation and communication of multi-tier platforms, and leverage simulation support for controllers and plants

    Modeling and Analysis of Automotive Cyber-physical Systems: Formal Approaches to Latency Analysis in Practice

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    Based on advances in scheduling analysis in the 1970s, a whole area of research has evolved: formal end-to-end latency analysis in real-time systems. Although multiple approaches from the scientific community have successfully been applied in industrial practice, a gap is emerging between the means provided by formally backed approaches and the need of the automotive industry where cyber-physical systems have taken over from classic embedded systems. They are accompanied by a shift to heterogeneous platforms build upon multicore architectures. Scien- tific techniques are often still based on too simple system models and estimations on important end-to-end latencies have only been tightened recently. To this end, we present an expressive system model and formally describe the problem of end-to-end latency analysis in modern automotive cyber-physical systems. Based on this we examine approaches to formally estimate tight end-to-end latencies in Chapter 4 and Chapter 5. The de- veloped approaches include a wide range of relevant systems. We show that our approach for the estimation of latencies of task chains dominates existing approaches in terms of tightness of the results. In the last chapter we make a brief digression to measurement analysis since measuring and simulation is an important part of verification in current industrial practice

    Design and implementation of WCET analyses : including a case study on multi-core processors with shared buses

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    For safety-critical real-time embedded systems, the worst-case execution time (WCET) analysis — determining an upper bound on the possible execution times of a program — is an important part of the system verification. Multi-core processors share resources (e.g. buses and caches) between multiple processor cores and, thus, complicate the WCET analysis as the execution times of a program executed on one processor core significantly depend on the programs executed in parallel on the concurrent cores. We refer to this phenomenon as shared-resource interference. This thesis proposes a novel way of modeling shared-resource interference during WCET analysis. It enables an efficient analysis — as it only considers one processor core at a time — and it is sound for hardware platforms exhibiting timing anomalies. Moreover, this thesis demonstrates how to realize a timing-compositional verification on top of the proposed modeling scheme. In this way, this thesis closes the gap between modern hardware platforms, which exhibit timing anomalies, and existing schedulability analyses, which rely on timing compositionality. In addition, this thesis proposes a novel method for calculating an upper bound on the amount of interference that a given processor core can generate in any time interval of at most a given length. Our experiments demonstrate that the novel method is more precise than existing methods.Die Analyse der maximalen Ausführungszeit (Worst-Case-Execution-Time-Analyse, WCET-Analyse) ist für eingebettete Echtzeit-Computer-Systeme in sicherheitskritischen Anwendungsbereichen unerlässlich. Mehrkernprozessoren erschweren die WCET-Analyse, da einige ihrer Hardware-Komponenten von mehreren Prozessorkernen gemeinsam genutzt werden und die Ausführungszeit eines Programmes somit vom Verhalten mehrerer Kerne abhängt. Wir bezeichnen dies als Interferenz durch gemeinsam genutzte Komponenten. Die vorliegende Arbeit schlägt eine neuartige Modellierung dieser Interferenz während der WCET-Analyse vor. Der vorgestellte Ansatz ist effizient und führt auch für Computer-Systeme mit Zeitanomalien zu korrekten Ergebnissen. Darüber hinaus zeigt diese Arbeit, wie ein zeitkompositionales Verfahren auf Basis der vorgestellten Modellierung umgesetzt werden kann. Auf diese Weise schließt diese Arbeit die Lücke zwischen modernen Mikroarchitekturen, die Zeitanomalien aufweisen, und den existierenden Planbarkeitsanalysen, die sich alle auf die Kompositionalität des Zeitverhaltens verlassen. Außerdem stellt die vorliegende Arbeit ein neues Verfahren zur Berechnung einer oberen Schranke der Menge an Interferenz vor, die ein bestimmter Prozessorkern in einem beliebigen Zeitintervall einer gegebenen Länge höchstens erzeugen kann. Unsere Experimente zeigen, dass das vorgestellte Berechnungsverfahren präziser ist als die existierenden Verfahren.Deutsche Forschungsgemeinschaft (DFG) as part of the Transregional Collaborative Research Centre SFB/TR 14 (AVACS
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