610 research outputs found

    Deep generative models for network data synthesis and monitoring

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    Measurement and monitoring are fundamental tasks in all networks, enabling the down-stream management and optimization of the network. Although networks inherently have abundant amounts of monitoring data, its access and effective measurement is another story. The challenges exist in many aspects. First, the inaccessibility of network monitoring data for external users, and it is hard to provide a high-fidelity dataset without leaking commercial sensitive information. Second, it could be very expensive to carry out effective data collection to cover a large-scale network system, considering the size of network growing, i.e., cell number of radio network and the number of flows in the Internet Service Provider (ISP) network. Third, it is difficult to ensure fidelity and efficiency simultaneously in network monitoring, as the available resources in the network element that can be applied to support the measurement function are too limited to implement sophisticated mechanisms. Finally, understanding and explaining the behavior of the network becomes challenging due to its size and complex structure. Various emerging optimization-based solutions (e.g., compressive sensing) or data-driven solutions (e.g. deep learning) have been proposed for the aforementioned challenges. However, the fidelity and efficiency of existing methods cannot yet meet the current network requirements. The contributions made in this thesis significantly advance the state of the art in the domain of network measurement and monitoring techniques. Overall, we leverage cutting-edge machine learning technology, deep generative modeling, throughout the entire thesis. First, we design and realize APPSHOT , an efficient city-scale network traffic sharing with a conditional generative model, which only requires open-source contextual data during inference (e.g., land use information and population distribution). Second, we develop an efficient drive testing system — GENDT, based on generative model, which combines graph neural networks, conditional generation, and quantified model uncertainty to enhance the efficiency of mobile drive testing. Third, we design and implement DISTILGAN, a high-fidelity, efficient, versatile, and real-time network telemetry system with latent GANs and spectral-temporal networks. Finally, we propose SPOTLIGHT , an accurate, explainable, and efficient anomaly detection system of the Open RAN (Radio Access Network) system. The lessons learned through this research are summarized, and interesting topics are discussed for future work in this domain. All proposed solutions have been evaluated with real-world datasets and applied to support different applications in real systems

    Anpassen verteilter eingebetteter Anwendungen im laufenden Betrieb

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    The availability of third-party apps is among the key success factors for software ecosystems: The users benefit from more features and innovation speed, while third-party solution vendors can leverage the platform to create successful offerings. However, this requires a certain decoupling of engineering activities of the different parties not achieved for distributed control systems, yet. While late and dynamic integration of third-party components would be required, resulting control systems must provide high reliability regarding real-time requirements, which leads to integration complexity. Closing this gap would particularly contribute to the vision of software-defined manufacturing, where an ecosystem of modern IT-based control system components could lead to faster innovations due to their higher abstraction and availability of various frameworks. Therefore, this thesis addresses the research question: How we can use modern IT technologies and enable independent evolution and easy third-party integration of software components in distributed control systems, where deterministic end-to-end reactivity is required, and especially, how can we apply distributed changes to such systems consistently and reactively during operation? This thesis describes the challenges and related approaches in detail and points out that existing approaches do not fully address our research question. To tackle this gap, a formal specification of a runtime platform concept is presented in conjunction with a model-based engineering approach. The engineering approach decouples the engineering steps of component definition, integration, and deployment. The runtime platform supports this approach by isolating the components, while still offering predictable end-to-end real-time behavior. Independent evolution of software components is supported through a concept for synchronous reconfiguration during full operation, i.e., dynamic orchestration of components. Time-critical state transfer is supported, too, and can lead to bounded quality degradation, at most. The reconfiguration planning is supported by analysis concepts, including simulation of a formally specified system and reconfiguration, and analyzing potential quality degradation with the evolving dataflow graph (EDFG) method. A platform-specific realization of the concepts, the real-time container architecture, is described as a reference implementation. The model and the prototype are evaluated regarding their feasibility and applicability of the concepts by two case studies. The first case study is a minimalistic distributed control system used in different setups with different component variants and reconfiguration plans to compare the model and the prototype and to gather runtime statistics. The second case study is a smart factory showcase system with more challenging application components and interface technologies. The conclusion is that the concepts are feasible and applicable, even though the concepts and the prototype still need to be worked on in future -- for example, to reach shorter cycle times.Eine große Auswahl von Drittanbieter-Lösungen ist einer der Schlüsselfaktoren für Software Ecosystems: Nutzer profitieren vom breiten Angebot und schnellen Innovationen, während Drittanbieter über die Plattform erfolgreiche Lösungen anbieten können. Das jedoch setzt eine gewisse Entkopplung von Entwicklungsschritten der Beteiligten voraus, welche für verteilte Steuerungssysteme noch nicht erreicht wurde. Während Drittanbieter-Komponenten möglichst spät -- sogar Laufzeit -- integriert werden müssten, müssen Steuerungssysteme jedoch eine hohe Zuverlässigkeit gegenüber Echtzeitanforderungen aufweisen, was zu Integrationskomplexität führt. Dies zu lösen würde insbesondere zur Vision von Software-definierter Produktion beitragen, da ein Ecosystem für moderne IT-basierte Steuerungskomponenten wegen deren höherem Abstraktionsgrad und der Vielzahl verfügbarer Frameworks zu schnellerer Innovation führen würde. Daher behandelt diese Dissertation folgende Forschungsfrage: Wie können wir moderne IT-Technologien verwenden und unabhängige Entwicklung und einfache Integration von Software-Komponenten in verteilten Steuerungssystemen ermöglichen, wo Ende-zu-Ende-Echtzeitverhalten gefordert ist, und wie können wir insbesondere verteilte Änderungen an solchen Systemen konsistent und im Vollbetrieb vornehmen? Diese Dissertation beschreibt Herausforderungen und verwandte Ansätze im Detail und zeigt auf, dass existierende Ansätze diese Frage nicht vollständig behandeln. Um diese Lücke zu schließen, beschreiben wir eine formale Spezifikation einer Laufzeit-Plattform und einen zugehörigen Modell-basierten Engineering-Ansatz. Dieser Ansatz entkoppelt die Design-Schritte der Entwicklung, Integration und des Deployments von Komponenten. Die Laufzeit-Plattform unterstützt den Ansatz durch Isolation von Komponenten und zugleich Zeit-deterministischem Ende-zu-Ende-Verhalten. Unabhängige Entwicklung und Integration werden durch Konzepte für synchrone Rekonfiguration im Vollbetrieb unterstützt, also durch dynamische Orchestrierung. Dies beinhaltet auch Zeit-kritische Zustands-Transfers mit höchstens begrenzter Qualitätsminderung, wenn überhaupt. Rekonfigurationsplanung wird durch Analysekonzepte unterstützt, einschließlich der Simulation formal spezifizierter Systeme und Rekonfigurationen und der Analyse der etwaigen Qualitätsminderung mit dem Evolving Dataflow Graph (EDFG). Die Real-Time Container Architecture wird als Referenzimplementierung und Evaluationsplattform beschrieben. Zwei Fallstudien untersuchen Machbarkeit und Nützlichkeit der Konzepte. Die erste verwendet verschiedene Varianten und Rekonfigurationen eines minimalistischen verteilten Steuerungssystems, um Modell und Prototyp zu vergleichen sowie Laufzeitstatistiken zu erheben. Die zweite Fallstudie ist ein Smart-Factory-Demonstrator, welcher herausforderndere Applikationskomponenten und Schnittstellentechnologien verwendet. Die Konzepte sind den Studien nach machbar und nützlich, auch wenn sowohl die Konzepte als auch der Prototyp noch weitere Arbeit benötigen -- zum Beispiel, um kürzere Zyklen zu erreichen

    Operational Technology Preparedness:A Risk-Based Safety Approach to Scoping Security Tests for Cyber Incident Response and Recovery

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    Following the advent of Industry 4.0, there have been significant benefits to industrial process optimisation through increased interconnectivity and the integration of Information Technology (IT) and Operational Technology (OT). However, this has also led to an increased attack surface for cyber threat actors to target. A growing number of cyber attacks on industrial environments, including Critical National Infrastructure, has, subsequently, been observed. In response, government and standardisation organisations alike have invested considerable resources in improving the cyber security of these environments. This includes response and recovery, often used as a last line of defence against cyber attacks. However, due to the unique design philosophies of Industrial Control Systems (ICS), several challenges exist for effectively securing these systems against digital threats. Through an analysis of standards and guidelines, used for assessing and improving cyber incident response and recovery capabilities, and stakeholder engagement on the implementation of these in practice, this thesis first identifies the challenges that exist when it comes to preparing for cyber incidents targeting ICS/OT environments. In particular, risk management, which involves identifying, evaluating, and prioritising risks and finding solutions to minimise, monitor, and control these, was found to be essential for improving preparation for cyber incidents. Assurance techniques are used as part of risk management to generate evidence for making claims of assurances about security. Alongside this, adversary-centric security tests such as penetration tests are used to evaluate and improve cyber resilience and incident response capabilities by emulating the actions of malicious actors. However, despite the benefits that these provide, they are currently not implemented to their full potential due to the safety and operational risks that exist in ICS/OT environments. This thesis contributes to academic and industry knowledge by proposing a framework that incorporates methods for identifying and quantifying the safety and operational risks of conducting adversary-centric security tests within ICS/OT environments. In understanding the risks, these engagements can be scoped using precise constraints so as to maximise the depth of testing while minimising risk to safety and the operational process. The framework is then evaluated through a qualitative study involving industry experts, confirming the framework's validity for implementation in practice

    Automotive Ethernet architecture and security: challenges and technologies

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    Vehicle infrastructure must address the challenges posed by today's advances toward connected and autonomous vehicles. To allow for more flexible architectures, high-bandwidth connections and scalability are needed to connect many sensors and electronic control units (ECUs). At the same time, deterministic and low latency is a critical and significant design requirement to support urgent real-time applications in autonomous vehicles. As a recent solution, the time-sensitive network (TSN) was introduced as Ethernet-based amendments in IEEE 802.1 TSN standards to meet those needs. However, it had hurdle to be overcome before it can be used effectively. This paper discusses the latest studies concerning the automotive Ethernet requirements, including transmission delay studies to improve worst-case end-to-end delay and end-to-end jitter. Also, the paper focuses on the securing Ethernet-based in-vehicle networks (IVNs) by reviewing new encryption and authentication methods and approaches

    Safe Halt as Fail-safe Concept for Automated Driving Systems

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    In order to guide a vehicle to the destination of a driving mission, various tasks shall be performed. These tasks include tactical and strategic planning of the driving mission and longitudinal and lateral vehicle motion control. Driver assistance systems support a human vehicle driver in performing these tasks. If faults occur in these systems, the vehicle driver is informed of the system limitations and shall take over the control of the vehicle. This fallback to a human driver is not an option in automated vehicles. If system limitations occur in these vehicles, a automated fallback level shall take over vehicle control. The automated driving system shall therefore be fail-safe. Fail-safe means that when faults occur, the automated driving system no longer has any function to perform a driving mission, but shall maintain the vehicle in a safe state and transition the vehicle into a Minimal Risk Condition (MRC). For this purpose, a situation-dependent MRC is selected. It is characterized by the global MRC concerning the length of the maneuver and the residual risk of the MRC itself. For the research project UNICARagil, the concept Safe Halt is proposed. This concept is intended to satisfy the requirements mentioned above. In the state of the art, an evaluation of this concept had not been included. This missing evaluation is performed in this thesis. The concept relies on pre-planned implicit emergency trajectories generated by a planning module. A unique concept feature is an independent environment perception system to ensure the Minimal Risk Maneuver (MRM) up to the MRC. Based on the pre-planned implicit emergency trajectory and the data of the independent environment perception system, Safe Halt plans trajectories up to the MRC. Thus, with this concept, even in the presence of failures to the environment perception system and to the strategic and tactical planning of an automated driving system, the safe state can be maintained, and the vehicle can be transitioned to a MRC. A methodology is presented to evaluate the concept of Safe Halt. For this purpose, the fault tolerance regimes of an automated vehicle are defined. Next, a reference implementation for Safe Halt is provided. For this, requirements for a Safe Halt in a generic automated driving system are identified first. These are supplemented by specific requirements from the application in the UNICARagil automated driving system. Finally, concepts and a synthesized reference solution are created for a Safe Halt in the UNICARagil ADS. The solution is verified with test criteria and test cases. A final evaluation of the Safe Halt concept shows a high effectiveness for the size of the subset of fault combinations of an automated driving system for which Safe Halt enables a fail-safe property. The requirements for Safe Halt are verified, and the specific requirements are met by the reference solution. The concept Safe Halt is thus suitable for an automated driving system to maintain a safe state. Validation of the concept in public road traffic is recommended

    General Course Catalog [2022/23 academic year]

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    General Course Catalog, 2022/23 academic yearhttps://repository.stcloudstate.edu/undergencat/1134/thumbnail.jp

    Jornadas Nacionales de Investigación en Ciberseguridad: actas de las VIII Jornadas Nacionales de Investigación en ciberseguridad: Vigo, 21 a 23 de junio de 2023

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    Jornadas Nacionales de Investigación en Ciberseguridad (8ª. 2023. Vigo)atlanTTicAMTEGA: Axencia para a modernización tecnolóxica de GaliciaINCIBE: Instituto Nacional de Cibersegurida

    Response Time Analysis for RT-MQTT Protocol Grounded on SDN

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    The current industry trend is to replace the use of custom components with standards-based Commercially available Off-The-Shelf (COTS) based hardware and protocols. Furthermore, the emergence of new industrial paradigms, such as Industry 4.0 and the Industrial Internet of Things, sets additional requirements regarding e.g. scale, transparency, agility, flexibility and efficiency. Therefore, in these domains, application layer protocols such as Message Queuing Telemetry Transport protocol (MQTT) are gaining popularity, in result of their simplicity, scalability, low resource-usage and decoupling between end nodes. However, such protocols were not designed for real-time applications, missing key features such as determinism and latency bounds. A recent work proposed extending MQTT with real-time services, taking advantage of Software Defined Networking (SDN) to manage the network resource. These extensions allow applications to specify real-time requirements that are then captured by a resource manager and used to reserve the necessary resources at the network layer. This paper shows that such MQTT extended architecture is analyzable from a worst-case timing perspective. We derive a system model that captures the real-time features and we present a response-time analysis to assess the schedulability of the real-time traffic. Finally, we validate the analysis with a set of experimental results
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