Titlebook: Computer Safety, Reliability, and Security; 40th International C Ibrahim Habli,Mark Sujan,Friedemann Bitsch Conference proceedings 2021 Spr

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Dignant

Evaluation Framework for Performance Limitation of Autonomous Systems Under Sensor Attackety analysis for scenario identification, and scenario-based simulation with sensor attack models embedded. Given an autonomous system model, we identify hazard scenarios caused by sensor attacks, and evaluate the performance limitations in the scenarios. We report on a prototype simulator for auton

Postulate

ISO/SAE 21434-Based Risk Assessment of Security Incidents in Automated Road Vehicles. Since the expected damage of a security incident also depends on the vehicle context, we include information such as speed, time, and traffic density into the risk computation. Based on the resulting risk value, the vehicle selects and realizes a compensating (safety) action. Finally, we discuss o

trigger

Safety Case Maintenance: A Systematic Literature Reviewthan the number of the actually impacted elements. Also, there is limited quantitative impact assessment. Further, existing approaches only address a few system change scenarios when providing guidelines for updating the safety case.

Collision

Safe Interaction of Automated Forklifts and Humans at Blind Corners in a Warehouse with Infrastructu mitigate these faults and gracefully degrades performance if required. Within our extensive evaluation, we use a warehouse simulation to verify our approach and to estimate the impact on an automated forklift’s performance.

surrogate

https://doi.org/10.1007/978-94-011-6361-3oth testing and formal verification; (3) the generation of contextually relevant counterexamples; and, through these, (4) the selection of DNN image classifiers suitable for the operational context (i) envisaged when a potentially safety-critical system is designed, or (ii) observed by a deployed sy

DIKE

The Beecham Manual for Family Practicerform in comparison to in-model approaches, we benchmarked them against deep ensembles, which can be considered the gold standard for in-model uncertainty estimation, as well as to the softmax outputs of a deep neural network as a baseline. Despite a slightly higher Brier score, the UW provides othe

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https://doi.org/10.1007/978-94-011-6361-3ety analysis for scenario identification, and scenario-based simulation with sensor attack models embedded. Given an autonomous system model, we identify hazard scenarios caused by sensor attacks, and evaluate the performance limitations in the scenarios. We report on a prototype simulator for auton

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