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 Khalilen Limba Engleză Paperback – 14 sep 2020
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
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.