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020 _a9783030545499
_9978-3-030-54549-9
024 7 _a10.1007/978-3-030-54549-9
_2doi
050 4 _aTK7885-7895
050 4 _aTK5105.5-5105.9
072 7 _aUK
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072 7 _aCOM067000
_2bisacsh
072 7 _aUK
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082 0 4 _a621.39
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082 0 4 _a004.6
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245 1 0 _aComputer Safety, Reliability, and Security
_h[electronic resource] :
_b39th International Conference, SAFECOMP 2020, Lisbon, Portugal, September 16-18, 2020, Proceedings /
_cedited by António Casimiro, Frank Ortmeier, Friedemann Bitsch, Pedro Ferreira.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXXIII, 450 p. 251 illus., 78 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aProgramming and Software Engineering,
_x2945-9168 ;
_v12234
505 0 _aSafety 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.
520 _aThis 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.
650 0 _aComputer engineering.
_910164
650 0 _aComputer networks .
_931572
650 0 _aArtificial intelligence.
_93407
650 0 _aSoftware engineering.
_94138
650 0 _aMicroprogramming .
_932081
650 0 _aCryptography.
_91973
650 0 _aData encryption (Computer science).
_99168
650 0 _aData protection.
_97245
650 1 4 _aComputer Engineering and Networks.
_9114963
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aSoftware Engineering.
_94138
650 2 4 _aControl Structures and Microprogramming.
_932083
650 2 4 _aCryptology.
_931769
650 2 4 _aData and Information Security.
_931990
700 1 _aCasimiro, António.
_eeditor.
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_9114964
700 1 _aOrtmeier, Frank.
_eeditor.
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_9114965
700 1 _aBitsch, Friedemann.
_eeditor.
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_9114966
700 1 _aFerreira, Pedro.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9114967
710 2 _aSpringerLink (Online service)
_9114968
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030545482
776 0 8 _iPrinted edition:
_z9783030545505
830 0 _aProgramming and Software Engineering,
_x2945-9168 ;
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_9114969
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