Machine Learning Safety Assurance -- Evaluation Framework for Performance Limitation under Sensor Attack -- Could We Relieve AI/ML Models of the Responsibility of Providing Dependable Uncertainty Estimates? A Study on Outside-Model Uncertainty Estimates -- Towards certification of a reduced footprint ACAS-Xu system: A hybrid ML-based solution -- Security Engineering -- IT design for resiliency using extreme value analysis -- Evaluating and Comparing Contextually Relevant Robustness for Neural Network Classifiers -- SAE 21434-based Risk Assessment of Security Incidents in Automated Road Vehicles -- Safety and Assurance Cases -- Automating the Assembly of Security Assurance Case -- Safety Case Maintenance: A Systematic Literature Review -- Towards Certified Analysis of Software Product Line Safety Cases -- Machine Learning Applications -- Safety assurance of machine learning for chassis control functions -- Safe Interaction of Automated Forklifts and Humans at Blind Cornersin a Warehouse with Infrastructure Sensors -- Machine Learning-based Fault Injection for Hazard Analysis and Risk Assessment -- Safety Validation and Simulation -- SASSI: Safety Analysis using Simulation-based Situation Coverage for Cobot Systems -- Attacks and Faults Injection in Self-Driving Agents on the Carla Simulator - Experience Report -- A Framework for Automated Quality Assurance and Documentation for Pharma 4.0 -- Fault Tolerance -- A Modular Approach To Non-Deterministic Dynamic Fault Trees -- Composition of Fault Forests.

This book constitutes the proceedings of the 40th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2021, which took place in York, UK, in September 2021. The 17 full papers included in this volume were carefully reviewed and selected from 76 submissions. They were organized in topical sections as follows: machine learning safety assurance; security engineering; safety and assurance cases; machine learning applications; safety validation and simulation; and fault tolerance.