6,184 research outputs found

    Enabling security checking of automotive ECUs with formal CSP models

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    Attack Defense Trees with Sequential Conjunction

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    On Provably Correct Decision-Making for Automated Driving

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    The introduction of driving automation in road vehicles can potentially reduce road traffic crashes and significantly improve road safety. Automation in road vehicles also brings several other benefits such as the possibility to provide independent mobility for people who cannot and/or should not drive. Many different hardware and software components (e.g. sensing, decision-making, actuation, and control) interact to solve the autonomous driving task. Correctness of such automated driving systems is crucial as incorrect behaviour may have catastrophic consequences. Autonomous vehicles operate in complex and dynamic environments, which requires decision-making and planning at different levels. The aim of such decision-making components in these systems is to make safe decisions at all times. The challenge of safety verification of these systems is crucial for the commercial deployment of full autonomy in vehicles. Testing for safety is expensive, impractical, and can never guarantee the absence of errors. In contrast, formal methods, which are techniques that use rigorous mathematical models to build hardware and software systems can provide a mathematical proof of the correctness of the system. The focus of this thesis is to address some of the challenges in the safety verification of decision-making in automated driving systems. A central question here is how to establish formal verification as an efficient tool for automated driving software development.A key finding is the need for an integrated formal approach to prove correctness and to provide a complete safety argument. This thesis provides insights into how three different formal verification approaches, namely supervisory control theory, model checking, and deductive verification differ in their application to automated driving and identifies the challenges associated with each method. It identifies the need for the introduction of more rigour in the requirement refinement process and presents one possible solution by using a formal model-based safety analysis approach. To address challenges in the manual modelling process, a possible solution by automatically learning formal models directly from code is proposed

    Towards a systematic security evaluation of the automotive Bluetooth interface

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    In-cabin connectivity and its enabling technologies have increased dramatically in recent years. Security was not considered an essential property, a mind-set that has shifted significantly due to the appearance of demonstrated vulnerabilities in these connected vehicles. Connectivity allows the possibility that an external attacker may compromise the security - and therefore the safety - of the vehicle. Many exploits have already been demonstrated in literature. One of the most pervasive connective technologies is Bluetooth, a short-range wireless communication technology. Security issues with this technology are well-documented, albeit in other domains. A threat intelligence study was carried out to substantiate this motivation and finds that while the general trend is towards increasing (relative) security in automotive Bluetooth implementations, there is still significant technological lag when compared to more traditional computing systems. The main contribution of this thesis is a framework for the systematic security evaluation of the automotive Bluetooth interface from a black-box perspective (as technical specifications were loose or absent). Tests were performed through both the vehicle’s native connection and through Bluetoothenabled aftermarket devices attached to the vehicle. This framework is supported through the use of attack trees and principles as outlined in the Penetration Testing Execution Standard. Furthermore, a proof-of-concept tool was developed to implement this framework in a semi-automated manner, to carry out testing on real-world vehicles. The tool also allows for severity classification of the results acquired, as outlined in the SAE J3061 Cybersecurity Guidebook for Cyber-Physical Vehicle Systems. Results of the severity classification are validated through domain expert review. Finally, how formal methods could be integrated into the framework and tool to improve confidence and rigour, and to demonstrate how future iterations of design could be improved is also explored. In conclusion, there is a need for systematic security testing, based on the findings of the threat intelligence study. The systematic evaluation and the developed tool successfully found weaknesses in both the automotive Bluetooth interface and in the vehicle itself through Bluetooth-enabled aftermarket devices. Furthermore, the results of applying this framework provide a focus for counter-measure development and could be used as evidence in a security assurance case. The systematic evaluation framework also allows for formal methods to be introduced for added rigour and confidence. Demonstrations of how this might be performed (with case studies) were presented. Future recommendations include using this framework with more test vehicles and expanding on the existing attack trees that form the heart of the evaluation. Further work on the tool chain would also be desirable. This would enable further accuracy of any testing or modelling required, and would also take automation of the entire process further

    A Model-Based Security Testing Approach for Automotive Over-The-Air Updates

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    Building a Credible Case for Safety: Waymo's Approach for the Determination of Absence of Unreasonable Risk

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    This paper presents an overview of Waymo's approach to building a reliable case for safety - a novel and thorough blueprint for use by any company building fully autonomous driving systems. A safety case for fully autonomous operations is a formal way to explain how a company determines that an AV system is safe enough to be deployed on public roads without a human driver, and it includes evidence to support that determination. It involves an explanation of the system, the methodologies used to develop it, the metrics used to validate it and the actual results of validation tests. Yet, in order to develop a worthwhile safety case, it is first important to understand what makes one credible and well crafted, and align on evaluation criteria. This paper helps enabling such alignment by providing foundational thinking into not only how a system is determined to be ready for deployment but also into justifying that the set of acceptance criteria employed in such determination is sufficient and that their evaluation (and associated methods) is credible. The publication is structured around three complementary perspectives on safety that build upon content published by Waymo since 2020: a layered approach to safety; a dynamic approach to safety; and a credible approach to safety. The proposed approach is methodology-agnostic, so that anyone in the space could employ portions or all of it

    Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles

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    With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria

    Measurable Safety of Automated Driving Functions in Commercial Motor Vehicles - Technological and Methodical Approaches

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    Fahrerassistenzsysteme sowie automatisiertes Fahren leisten einen wesentlichen Beitrag zur Verbesserung der Verkehrssicherheit von Kraftfahrzeugen, insbesondere von Nutzfahrzeugen. Mit der Weiterentwicklung des automatisierten Fahrens steigt hierbei die funktionale LeistungsfĂ€higkeit, woraus Anforderungen an neue, gesamtheitliche Erprobungskonzepte entstehen. Um die Absicherung höherer Stufen von automatisierten Fahrfunktionen zu garantieren, sind neuartige Verifikations- und Validierungsmethoden erforderlich. Ziel dieser Arbeit ist es, durch die Aggregation von Testergebnissen aus wissensbasierten und datengetriebenen Testplattformen den Übergang von einer quantitativen Kilometerzahl zu einer qualitativen Testabdeckung zu ermöglichen. Die adaptive Testabdeckung zielt somit auf einen Kompromiss zwischen Effizienz- und EffektivitĂ€tskriterien fĂŒr die Absicherung von automatisierten Fahrfunktionen in der Produktentstehung von Nutzfahrzeugen ab. Diese Arbeit umfasst die Konzeption und Implementierung eines modularen Frameworks zur kundenorientierten Absicherung automatisierter Fahrfunktionen mit vertretbarem Aufwand. Ausgehend vom Konfliktmanagement fĂŒr die Anforderungen der Teststrategie werden hochautomatisierte TestansĂ€tze entwickelt. Dementsprechend wird jeder Testansatz mit seinen jeweiligen Testzielen integriert, um die Basis eines kontextgesteuerten Testkonzepts zu realisieren. Die wesentlichen BeitrĂ€ge dieser Arbeit befassen sich mit vier Schwerpunkten: * ZunĂ€chst wird ein Co-Simulationsansatz prĂ€sentiert, mit dem sich die SensoreingĂ€nge in einem Hardware-in-the-Loop-PrĂŒfstand mithilfe synthetischer Fahrszenarien simulieren und/ oder stimulieren lassen. Der vorgestellte Aufbau bietet einen phĂ€nomenologischen Modellierungsansatz, um einen Kompromiss zwischen der ModellgranularitĂ€t und dem Rechenaufwand der Echtzeitsimulation zu erreichen. Diese Methode wird fĂŒr eine modulare Integration von Simulationskomponenten, wie Verkehrssimulation und Fahrdynamik, verwendet, um relevante PhĂ€nomene in kritischen Fahrszenarien zu modellieren. * Danach wird ein Messtechnik- und Datenanalysekonzept fĂŒr die weltweite Absicherung von automatisierten Fahrfunktionen vorgestellt, welches eine Skalierbarkeit zur Aufzeichnung von Fahrzeugsensor- und/ oder Umfeldsensordaten von spezifischen Fahrereignissen einerseits und permanenten Daten zur statistischen Absicherung und Softwareentwicklung andererseits erlaubt. Messdaten aus lĂ€nderspezifischen Feldversuchen werden aufgezeichnet und zentral in einer Cloud-Datenbank gespeichert. * Anschließend wird ein ontologiebasierter Ansatz zur Integration einer komplementĂ€ren Wissensquelle aus Feldbeobachtungen in ein Wissensmanagementsystem beschrieben. Die Gruppierung von Aufzeichnungen wird mittels einer ereignisbasierten Zeitreihenanalyse mit hierarchischer Clusterbildung und normalisierter Kreuzkorrelation realisiert. Aus dem extrahierten Cluster und seinem Parameterraum lassen sich die Eintrittswahrscheinlichkeit jedes logischen Szenarios und die Wahrscheinlichkeitsverteilungen der zugehörigen Parameter ableiten. Durch die Korrelationsanalyse von synthetischen und naturalistischen Fahrszenarien wird die anforderungsbasierte Testabdeckung adaptiv und systematisch durch ausfĂŒhrbare Szenario-Spezifikationen erweitert. * Schließlich wird eine prospektive Risikobewertung als invertiertes Konfidenzniveau der messbaren Sicherheit mithilfe von SensitivitĂ€ts- und ZuverlĂ€ssigkeitsanalysen durchgefĂŒhrt. Der Versagensbereich kann im Parameterraum identifiziert werden, um die Versagenswahrscheinlichkeit fĂŒr jedes extrahierte logische Szenario durch verschiedene Stichprobenverfahren, wie beispielsweise die Monte-Carlo-Simulation und Adaptive-Importance-Sampling, vorherzusagen. Dabei fĂŒhrt die geschĂ€tzte Wahrscheinlichkeit einer Sicherheitsverletzung fĂŒr jedes gruppierte logische Szenario zu einer messbaren Sicherheitsvorhersage. Das vorgestellte Framework erlaubt es, die LĂŒcke zwischen wissensbasierten und datengetriebenen Testplattformen zu schließen, um die Wissensbasis fĂŒr die Abdeckung der Operational Design Domains konsequent zu erweitern. Zusammenfassend zeigen die Ergebnisse den Nutzen und die Herausforderungen des entwickelten Frameworks fĂŒr messbare Sicherheit durch ein Vertrauensmaß der Risikobewertung. Dies ermöglicht eine kosteneffiziente Erweiterung der ValiditĂ€t der TestdomĂ€ne im gesamten Softwareentwicklungsprozess, um die erforderlichen Testabbruchkriterien zu erreichen

    Parametric Design, Modeling, and Optical Evaluation of Retroreflective Prismatic Structures

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    Retroreflectors (RR) are defined as passive optical structures that redirect incident light to its originating source. Specific types of retroreflectors called inverted cubes (ICs) function through total internal reflection (TIR) and are used in various applications such as measurement tools, traffic signs and automotive rear and side lighting. This thesis aims to model, analyze, fabricate and study a novel type of IC retroreflectors called right triangular prism (RTP). A parametric approach is used to model existing IC geometries from a generic unit cube and is then implemented to model the novel RTP geometry. Those elements are then tested by optical simulation software in single element and areal forms and their performances are compared. Moreover, fabricated prototype arrays of RTPs were separately tested using a digital lux meter and a luminance imaging system. Both virtual and physical optical experimentation proved that the newly designed RTP structure is indeed functional and have the potential to be used in many applications
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