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Trust, Privacy and Security in Digital Business: 17th International Conference, TrustBus 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings de Stefanos Gritzalis

Trust, Privacy and Security in Digital Business: 17th International Conference, TrustBus 2020, Bratislava, Slovakia, September 14–17, 2020, Proceedings: Lecture Notes in Computer Science, cartea 12395

Editat de Stefanos Gritzalis, Edgar R. Weippl, Gabriele Kotsis, A Min Tjoa, Ismail Khalil
en Limba Engleză Paperback – 14 sep 2020
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 conference was held virtually due to the COVID-19 pandemic.
The 11 full and 4 short papers presented were carefully reviewed and selected from 28 submissions. The papers are organized in the following topical sections: blockchain, cloud security/hardware; economics/privacy; human aspects; privacy; privacy and machine learning; trust.
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Specificații

ISBN-13: 9783030589851
ISBN-10: 3030589854
Pagini: 214
Ilustrații: X, 235 p. 69 illus., 30 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.35 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Security and Cryptology

Locul publicării:Cham, Switzerland

Cuprins

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.