17 research outputs found

    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

    Secured information dissemination and misbehavior detection in VANETs

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    In a connected vehicle environment, the vehicles in a region can form a distributed network (Vehicular Ad-hoc Network or VANETs) where they can share traffic-related information such as congestion or no-congestion with other vehicles within its proximity, or with a centralized entity via. the roadside units (RSUs). However, false or fabricated information injected by an attacker (or a malicious vehicle) within the network can disrupt the decision-making process of surrounding vehicles or any traffic-monitoring system. Since in VANETs the size of the distributed network constituting the vehicles can be small, it is not difficult for an attacker to propagate an attack across multiple vehicles within the network. Under such circumstances, it is difficult for any traffic monitoring organization to recognize the traffic scenario of the region of interest (ROI). Furthermore, even if we are able to establish a secured connected vehicle environment, an attacker can leverage the connectivity of individual vehicles to the outside world to detect vulnerabilities, and disrupt the normal functioning of the in-vehicle networks of individual vehicles formed by the different sensors and actuators through remote injection attacks (such as Denial of Service (DoS)). Along this direction, the core contribution of our research is directed towards secured data dissemination, detection of malicious vehicles as well as false and fabricated information within the network. as well as securing the in-vehicle networks through improvisation of the existing arbitration mechanism which otherwise leads to Denial of Service (DoS) attacks (preventing legitimate components from exchanging messages in a timely manner). --Abstract, page iv

    Timing model derivation : pipeline analyzer generation from hardware description languages

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    Safety-critical systems are forced to finish their execution within strict deadlines so that worst-case execution time (WCET) guarantees are a crucial part of their verification. Timing models of the analyzed hardware form the basis for static analysis-based approaches like the aiT WCET analyzer. Currently, timing models are hand-crafted based on frequently incorrect documentation causing the process to be error-prone and time-consuming. This thesis bridges the gap between automatic hardware synthesis and WCET analysis development by introducing a process for the derivation of timing models from VHDL specifications. We propose a set of transformations and abstractions to reduce the hardware design\u27s complexity enabling the generation of efficient and provably correct WCET analyzers. They employ an abstract interpretation-based simulation of program executions based on a defined abstract simulation semantics. We have defined workflow patterns showing how to gradually apply the derivation process to VHDL models, thereby removing timing-irrelevant constructs. Interval property checking is used to validate the transformations. A further contribution of this thesis is the implementation of a tool set that realizes the introduced derivation process and shows its applicability to non-trivial industrial designs in experimental evaluations. Influences on design choices to the quality of the derived timing model are presented building an informal predictability notion for VHDL.Sicherheits-kritische Systeme unterliegen oft der Einhaltung strikter Laufzeitschranken, weshalb zur Verifikation sichere Obergrenzen der Laufzeit im schlimmsten Fall (WCET) bestimmt werden. Zeitmodelle der analysierten Hardware sind hierbei die Grundlage für auf statischen Analysen basierende Verfahren. Aktuell werden solche Modelle händisch aus Handbüchern extrahiert, ein sehr zeitaufwändiger und fehleranfälliger Prozess. Diese Arbeit schlägt eine Brücke zwischen automatischer Hardware-Synthese und der Entwicklung von WCET-Analysen durch die Einführung eines Ableitungsprozesses von Zeitmodellen aus VHDL-Spezifikationen. Transformationen und Abstraktionen werden zur Komplexitätsreduktion eingesetzt, um die Erzeugung von effizienten und beweisbar korrekten Analysatoren zu ermöglichen. Selbige bedienen sich abstrakter Interpretation von Programmausführungen basierend auf einer Simulations-Semantik. Definierte Arbeitsabläufe zeigen, wie man die Ableitung schrittweise auf VHDL-Modellen umsetzt und dadurch für das Zeitverhalten irrelevante Teile des Modells entfernt. Interval Property Checking gewährleistet hierbei, dass die Transformationen semantik-erhaltend sind. Eine Tool-Implementierung realisiert den vorgestellen Ableitungsprozess und unterstreicht seine Anwendbarkeit auf komplexe industrielle Designs durch experimentelle untersuchungen. Außerdem werden VHDL-Designentscheidungen hinsicht ihres Einflusses auf die Qualität des abgeleiteten Zeitmodells betrachtet

    Kollektive Perzeption in fahrzeugbasierten Ad-hoc Netzwerken

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    In combination with the current developments in the area of automatically driving vehicles, the introduction of inter-vehicle communication plays a crucial role for realising the long-term objective of what is known as cooperative driving. A cornerstone for the expansion of automated vehicles is their thorough understanding of the current driving environment. For this purpose, each vehicle generates an environment model containing information about other perceived traffic participants and objects. Local perception sensors are important data providers for this model, as they contribute implicit knowledge about the environment. In combination with a direct communication link between traffic participants, explicit knowledge can be added to the environment model as well. The key concept developed within this thesis is called Collective Perception: it focuses on sharing data gathered by local perception sensors of one vehicle with other traffic participants by means of inter-vehicle communication. As a result of this concept, future applications relying on a comprehensive understanding of the current driving environment are made feasible. The analyses presented in this thesis employ a vehicular ad-hoc network (VANET) based on the standardised framework of the European IEEE 802.11p-based ITS G5 protocol stack for inter-vehicle communication. The effectiveness of the technology relies on an existing communication link between a sufficient number of communication partners - the critical mass. The expansion of inter-vehicle communication, however, can be supported by capacitating indirect effects. Collective Perception is one representative of these effects, as the information density within the network between the vehicles is increased, even at low market penetration rates. At the core of Collective Perception stands the introduction of a message format which serves as a vehicle for the exchange of sensor data within a VANET. The development of the message is influenced by two perspectives: First, the vehicle perspective affects the relevant contents of the message required by data-fusion processes and application algorithms. Second, from the network perspective, constraints resulting from the network stack and effects caused by congestion control mechanisms have to be considered. This thesis addresses both perspectives to develop a holistic concept for exchanging sensor data within a VANET.Im Zusammenhang mit den aktuellen Entwicklungen im Themenbereich automatisch fahrender Fahrzeuge spielt die Einführung der Fahrzeug-zu-Fahrzeug-Kommunikation eine zunehmend wichtige Rolle, um langfristig kooperatives Fahren zu realisieren. Eine Voraussetzung für dessen Umsetzung ist dabei die umfassende Wahrnehmung der aktuellen Fahrumgebung. Jedes Fahrzeug erstellt dafür ein sogenanntes Umfeldmodell, welches Informationen über andere Verkehrsteilnehmer und Objekte beinhaltet. Eine wichtige Datenquelle für dieses Modell sind zum einen lokale Umfeldsensoren, welche implizites Wissen über die aktuelle Fahrumgebung beisteuern. Zum anderen kann dem Umfeldmodell bei einer direkten Kommunikationsverbindung mit anderen Verkehrsteilnehmern auch explizites Wissen hinzugefügt werden. Im Rahmen dieser Arbeit wird ein Konzept zur Realisierung der sogenannten kollektiven Wahrnehmung entwickelt: Hierbei wird Fahrzeugen der Austausch lokaler Sensordaten mit anderen Verkehrsteilnehmern unter Verwendung der Fahrzeug-zu-Fahrzeug-Kommunikation ermöglicht. Somit können zukünftige Fahrerassistenzfunktionen auf ein umfassenderes Umfeldmodell zugreifen. Den im Rahmen der Arbeit durchgeführten Analysen liegt ein fahrzeugbasiertes Ad-hoc Netzwerk zugrunde, welches auf dem europäischen IEEE 802.11p basierten ITS G5 Protokollstapel beruht. Die Effektivität der Technologie fußt hierbei auf der Existenz der sogenannten kritischen Masse: Eine ausreichende Anzahl an Kommunikationspartnern muss zugegen sein, damit der Technologie ein Nutzen zugemessen werden kann. Die Verbreitung der Technologie kann jedoch durch indirekte Effekte unterstützt werden. Die kollektive Wahrnehmung ist ein Repräsentant dieser indirekten Effekte, da die Informationsdichte in dem zwischen den Fahrzeugen bestehenden Netzwerk selbst bei niedrigen Marktausstattungsraten erhöht wird. Im Rahmen der Arbeit wird daher ein neues Nachrichtenformat entwickelt, welches von zwei Perspektiven beeinflusst: Die Sicht der fahrzeugseitigen Assistenzsysteme und deren Datenfusionsalgorithmen beeinflusst die notwendigen Inhalte der Nachricht. Weiterhin werden aus der Netzwerksicht durch Mechanismen wie denen der Lastkontrolle und den bestehenden Nachrichtengrößenbeschränkungen spezifische Anforderungen gestellt. Beide Untersuchungen werden dabei in der Arbeit zur Erstellung eines ganzheitlichen Konzeptes für die kollektive Wahrnehmung verbunden

    Enhancing the Automotive E/E Architecture Utilising Container-Based Electronic Control Units

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    Over the past 40 years, with the advent of computing technology and embedded systems, such as Electronic Control Units (ECUs), cars have moved from solely mechanical control to predominantly digital control. Whilst improvements have been realised in terms of passenger safety and vehicle efficiency, there are several issues currently facing the automotive industry as a result of the rising number of ECUs. These include greater demands placed on power, increased vehicle weight, complexities of hardware and software, dependency on software, software life expectancy, ad-hoc methods concerning automotive software updates, and rising costs for the vehicle manufacturer and consumer. As the modern-day motor car enters the autonomous age, these issues are predicted to increase because there will be an even greater reliance on computing hardware and software technology to support these new driving functions. To address the issues highlighted above, a number of solutions that aid hardware consolidation and promote software reusability have been proposed. However, these depend on bespoke embedded hardware and there remains a lack of clearly defined mechanisms through which to update ECU software. This research moves away from these current practices and identifies many similarities between the datacentre and the automotive Electronic and Electrical (E/E) architecture, demonstrating that virtualisation technologies, which have provided many benefits to the datacentre, can be replicated within an automotive context. Specifically, the research presents a comprehensive study of the Central Processor Unit (CPU) and memory resources required and consumed to support a container-based ECU automotive function. The research reveals that lightweight container virtualisation offers many advantages. A container-based ECU can promote consolidation and enhance the automotive E/E architecture through power, weight and cost savings, as well as enabling a robust mechanism to facilitate future software updates throughout the lifetime of a vehicle. Furthermore, this research demonstrates there are opportunities to adopt this new research methodology within both the automotive industry and industries that utilise embedded systems, more broadly

    Deterministic ethernet in a safety critical environment

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    This thesis explores the concept of creating safety critical networks with low congestion and latency (known as critical networking) for real time critical communication (safety critical environment). Critical networking refers to the dynamic management of all the application demands in a network within all available network bandwidth, in order to avoid congestion. Critical networking removes traffic congestion and delay to provide quicker response times. A Deterministic Ethernet communication system in a Safety Critical environment addresses the disorderly Ethernet traffic condition inherent in all Ethernet networks. Safety Critical environment means both time critical (delay sensitive) and content critical (error free). Ethernet networks however do not operate in a deterministic fashion, giving rise to congestion. To discover the common traffic patterns that cause congestion a detailed analysis was carried out using neural network techniques. This analysis has investigated the issues associated with delay and congestion and identified their root cause, namely unknown transmission conditions. The congestion delay, and its removal, was explored in a simulated control environment in a small star network using the Air-field communication standard. A Deterministic Ethernet was created and implemented using a Network Traffic Oscillator (NTO). NTO uses Critical Networking principles to transform random burst application transmission impulses into deterministic sinusoid transmissions. It is proved that the NTO has the potential to remove congestion and minimise latency. Based on its potential, it is concluded that the proposed Deterministic Ethernet can be used to improve network security as well as control long haul communication

    University of Windsor Undergraduate Calendar 2021 Spring

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    https://scholar.uwindsor.ca/universitywindsorundergraduatecalendars/1015/thumbnail.jp

    University of Windsor Undergraduate Calendar 2023 Winter

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    https://scholar.uwindsor.ca/universitywindsorundergraduatecalendars/1020/thumbnail.jp
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