Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops

Using Assurance Cases to Prevent Malicious Behaviour from Targeting Safety Vulnerabilities.- Constructing Security Cases Based on Formal Verification of Security Requirements in Alloy.-Assurance Cases for Timing Properties of Automotive TSN Networks.- Toward Dependability Assurance Framework for Automated Driving Systems.- A Quantitative Approach for System of Systems' Resilience Analyzing Based on Archimate.- Towards DO-178C Compliance of a Secure Product.- The Need for Threat Modelling in Unmanned Aerial Systems.- Using Runtime information of controllers for safe adaptation at runtime: a Process Mining approach.- Safety and Robustness for Deep Neural Networks: An Automotive Use Case.- Towards Dependable Integration Concepts for AI-based Systems.- A Methodology for the Qualification of Operating Systems and Hypervisors for the deployment in IoT devices.- Computer-Aided Generation of Assurance Cases.- RACK: A Semantic Model and Triplestore for Curation of Assurance Case Evidence.- Patterns for Integrating NIST 800-53 Controls into Security Assurance Cases.- Analyzing Origins of Safety and Security Interactions using Feared Events Trees and Multi-level Model.- Utilising Redundancy to Enhance Security of Safety-Critical Systems.- Reliability Evaluation of Autonomous Transportation System Architecture Based on Markov Chain.- Uncertainty Quantification for Semantic Segmentation Models via Evidential Reasoning.- Research on the Reliability of High-Speed Railway Dispatching and Commanding Personnel with Multi Physiological Signals.- Research on Brain Load prediction based on machine learning for High-speed Railway.- Paired Safety Rule Structure for Human-machine Cooperation with Feature Update and Evolution.- Towards an Effective Generation of Functional Scenarios for AVs to Guide Sampling.- Rear-end Collision Risk Analysis for Autonomous Driving.- Improving road traffic safety and performance - barriers and directions towards cooperative automated vehicles.- A Group-Level Learning Approach Using Logistic Regression for Fairer Decisions.- Conformal Prediction and Uncertainty Wrapper: What Statistical Guarantees Can You Get for Uncertainty Quantification in Machine Learning.- AIMOS: Metamorphic Testing of AI - An Industrial Application.- AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms.- A Reasonable Driver Standard for Automated Vehicle Safety.- Structuring Research Related to Dynamic Risk Management for Autonomous Systems.- Towards Safe Machine Learning Lifecycles with ESG Model Cards.- Towards Deep Anomaly Detection with Structured Knowledge Representations.- Evaluating and Increasing Segmentation Robustness in CARLA.- Safety Integrity Levels for Artificial Intelligence.- Can Large Language Models assist in Hazard Analysis.- Contextualised Out-of-Distribution Detection using Pattern Identification.