Computer Safety, Reliability, and Security (eBook, PDF)

39th International Conference, SAFECOMP 2020, Lisbon, Portugal, September 16-18, 2020, Proceedings
Redaktion: Casimiro, António; Ferreira, Pedro; Bitsch, Friedemann; Ortmeier, Frank

• Format: PDF

Produktbeschreibung

This book constitutes the proceedings of the 39th International Conference on Computer Safety, Reliability and Security, SAFECOMP 2020, held in Lisbon, Portugal, in September 2020.*

The 27 full and 2 short papers included in this volume were carefully reviewed and selected from 116 submissions. They were organized in topical sections named: safety cases and argumentation; formal verification and analysis; security modelling and methods; assurance of learning-enabled systems; practical experience and tools; threat analysis and risk mitigation; cyber-physical systems security; and fault injection and fault tolerance.

*The conference was held virtually due to the COVID-19 pandemic.

The chapter 'Assurance Argument Elements for Off-the-Shelf, Complex Computational Hardware' is available open access under an Open Government License 3.0 via link.springer.com.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 450
• Erscheinungstermin: 19. August 2020
• Englisch
• ISBN-13: 9783030545499
• Artikelnr.: 60035610

Inhaltsangabe

Safety Cases and Argumentation.- Synthesis of Runtime Safety Monitors for Cyber-Physical Systems with Digital Dependability Identities.- Systematic Evaluation of (Safety) Assurance Cases.- Just Enough Formality in Assurance Argument Structures.- Towards Recertification of Modular Updates in Integrated Maritime Systems of Systems.- Formal Verification and Analysis.- A functional verification methodology for highly configurable, continuously operating safety-critical FPGA designs: Applied to the CERN RadiatiOn Monitoring Electronics (CROME).- A Compositional Semantics for Repairable BDMPs.- Model-Based Safety Analysis of Mode Transitions.- Efficient Translation of Safety LTL to DFA using Symbolic Automata Learning and Inductive Inference.- Security Modelling and Methods.- Automated Attacker Synthesis for Distributed Protocols.- An Attacker Modeling Framework for the Assessment of Cyber-Physical Systems Security.- Predicting Railway Signalling Commands using Neural Networks for Anomaly Detection.- Automated Anomaly Detection in CPS Log Files - A Time Series Clustering Approach.- Assurance of Learning-enabled Systems.- Assuring the Safety of Machine Learning for Pedestrian Detection at Crossings.- Safety-Aware Hardening of 3D Object Detection Neural Network Systems.- Model-Centered Assurance for Autonomous Systems.- A Safety Framework for Critical Systems Utilising Deep Neural Networks.- Assurance Argument Elements for Off-the-Shelf, Complex Computational Hardware.- Quantifying Assurance in Learning-enabled Systems.- Practical Experience and Tools.- Cyber Security of Neural Networks in Medical Devices.- FASTEN.Safe: A Model-driven Engineering Tool to Experiment with Checkable Assurance Cases.- Threat Analysis and Risk Mitigation.- On Validating Attack Trees with Attack Effects.- Safety meets Security: Using ISA-62443 for a Highly Automated Road Vehicle.- Threat Analysis Framework for Safety Architectures in SCDL.- Cyber-Physical Systems Security.- Efficient Load-Time Diversity for an Embedded Real-Time Operating System.- Towards an Automated Exploration of Secure IoT/CPS Design-Variants.- Securing Electric Vehicle Charging Systems through Component Binding.- Fault Injection and Fault Tolerance.- Using Hardware-In-Loop-Based Fault Injection to Determine the Effects of Control Flow Errors in Industrial Control Programs.- On Configuring a Testbed for Dependability Experiments: Guidelines and Fault Injection Case Study.- A Classification of Faults Covering the Human-Computer Interaction Loop.