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Titlebook: Computer Safety, Reliability, and Security; SAFECOMP 2019 Worksh Alexander Romanovsky,Elena Troubitsyna,Friedemann Conference proceedings

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发表于 2025-3-21 16:21:38 | 显示全部楼层 |阅读模式
书目名称Computer Safety, Reliability, and Security
副标题SAFECOMP 2019 Worksh
编辑Alexander Romanovsky,Elena Troubitsyna,Friedemann
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Safety, Reliability, and Security; SAFECOMP 2019 Worksh Alexander Romanovsky,Elena Troubitsyna,Friedemann  Conference proceedings
描述.This book constitutes the proceedings of the Workshops held in conjunction with SAFECOMP 2019, 38th International Conference on Computer Safety, Reliability and Security, in September 2019 in Turku, Finland. ..The 32 regular papers included in this volume were carefully reviewed and selected from 43 submissions; the book also contains two invited papers. The workshops included in this volume are:..ASSURE 2019:. 7th International Workshop on Assurance Cases for Software-Intensive Systems..DECSoS 2019:. 14th ERCIM/EWICS/ARTEMIS Workshop on Dependable Smart Embedded and Cyber-Physical Systems and Systems-of-Systems..SASSUR 2019:. 8th International Workshop on Next Generation of System Assurance Approaches for Safety-Critical Systems..STRIVE 2019:. Second International Workshop on Safety, securiTy, and pRivacy In automotiVe systEms..WAISE 2019:. Second International Workshop on Artificial Intelligence Safety Engineering.. .
出版日期Conference proceedings 2019
关键词artificial intelligence; authentication; autonomous vehicles; computer vision; cryptography; data securit
版次1
doihttps://doi.org/10.1007/978-3-030-26250-1
isbn_softcover978-3-030-26249-5
isbn_ebook978-3-030-26250-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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发表于 2025-3-21 20:57:46 | 显示全部楼层
A Modelling Approach for System Life Cycles Assurances understood than the former, due partly to the lack of consensus on what a ‘life cycle model’ is. This paper proposes a formulation of life cycle models that aims to clarify what it means to assure that a life cycle so modelled achieves expected outcomes. Dependent Petri Net life cycle model is a v
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Comparative Evaluation of Security Fuzzing Approachesential for exposing vulnerabilities and the expected effort required to do so. These preliminary considerations based on abstract reasoning and engineering judgement are subsequently confronted with experimental evaluations based on the application of three different fuzzing tools characterized by d
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Assuring Compliance with Protection Profiles with ThreatGetrting an iterative and model-based risk management process. We explain the modeling and operation of ThreatGet and how it can be used for security by design. As a specific use case, we demonstrate how ThreatGet can assess compliance with a protection profile.
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Combined Approach for Safety and Security) have become increasingly complex. We can not consider these dependability attributes in isolation, therefore, combined approaches for safety, security and other attributes are required. In this document, we provide a matrix based approach (inspired from ANP (Analytical Network Process)) for combin
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Towards Integrated Quantitative Security and Safety Risk Assessment used for combined risk management. This paper presents the existing gaps, based on an overview of available methods, which is followed by the proposal towards a solution to achieve coordinated risk management by applying a quantitative security risk assessment methodology. This methodology extends
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Potential Use of Safety Analysis for Risk Assessments in Smart City Sensor Network Applicationsthods from dependability engineering could be used to identify potential risk relating to safety and security of such applications. The demonstration object of this paper is a sensor network for air quality analysis and dynamic traffic control based on these data.
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Increasing Safety of Neural Networks in Medical Devicesetworks are used to detect certain medical/decease indications. For example, a potential imminent asthma insult is detected based e.g. on breathing pattern, heart rate, and a few optional additional parameters. The patient receives a warning message and can either change his behavior and/or take som
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