Del 12395 - Lecture Notes in Computer Science

Trust, Privacy and Security in Digital Business

17th International Conference, TrustBus 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings

Häftad, Engelska, 2020

AvStefanos Gritzalis,Edgar R. Weippl,Gabriele Kotsis,A Min Tjoa,Ismail Khalil,Edgar Weippl

709 kr

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This book constitutes the refereed proceedings of the 17th International Conference on Trust, Privacy and Security in Digital Business, TrustBus 2020, held in Bratislava, Slovakia, in September 2020. The 11 full and 4 short papers presented were carefully reviewed and selected from 28 submissions.

Produktinformation

Utgivningsdatum2020-09-14
Mått155 x 235 x 14 mm
Vikt382 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor235
FörlagSpringer Nature Switzerland AG
ISBN9783030589851

Tillhör följande kategorier

Tillämpad datateknik inom Data och IT
Hårdvara inom Data och IT
Artificiell intelligens inom Data och IT
Nätverk och kommunikation inom Data och IT
Referensverk och tvärvetenskap inom Samhälle och politik
IT-säkerhet inom Data och IT

Analysis of uPort Open, an identity management blockchain-based solution.- Cloud Computing Framework for e-Health Security Requirements & Security Policy Rules Case Study: A European Cloud-based Health System.- On the Suitability of Using SGX for Secure Key Storage in the Cloud.- Employment of Secure Enclaves in CheatDetection Hardening.- SECONDO: A Platform for Cybersecurity Investments and Cyber Insurance Decisions.- Are Sensor Based Business Models a Threat to Privacy: The Case Of Pay-How-Your-Drive Insurance Models.- Microtargeting or Microphishing? Phishing Unveiled.- Privacy - Preserving Service Composition with Enhanced Flexibility and Efficiency.- An empirical Investigation of the right to explanation under GDPR in insurance.- Measuring users’ socio-contextual attributes for Self-Adaptive Privacy within Cloud-Computing Environments.- Empowering Users Through a PrivacyMiddleware Watchdog.- Utility Requirement Description for Utility-preserving and Privacy-respecting Data Pseudonymization.- DEFeND DSM: A Data Scope Management Service for Model-Based Privacy by Design GDPR Compliance.- A Distributed Trust Framework for Privacy-Preserving Machine Learning.- A Fuzzy Trust Model for Autonomous Entities Acting in Pervasive Computing.

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