Privacy and Identity Management. Fairness, Accountability, and Transparency in the Age of Big Data
Description
This book contains selected papers presented at the 13th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Vienna, Austria, in August 2018.
The 10 full papers included in this volume were carefully reviewed and selected from 27 submissions. Also included are reviewed papers summarizing the results of workshops and tutorials that were held at the Summer School as well as papers contributed by several of the invited speakers. The papers combine interdisciplinary approaches to bring together a host of perspectives: technical, legal, regulatory, socio-economic, social, societal, political, ethical, anthropological, philosophical, historical, and psychological.
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A Causal Bayesian Networks Viewpoint on Fairness.- Sharing is caring, a boundary object approach to mapping and discussing personal data processing.- Who You Gonna Call When There's Something Wrong in Your Processing? Risk Assessment and Data Breach Notications in Practice.- Design and Security Assessment of Usable Multi-Factor Authentication and Single Sign-On Solutions for Mobile Applications: A Workshop Experience Report.- Towards Empowering the Human for Privacy Online.- Trust and Distrust: On Sense and Nonsense in Big Data.- GDPR transparency requirements and data privacy vocabularies.- Glycos: the basis for a peer-to-peer, private online social network.- GDPR and the Concept of Risk: The Role of risk, the Scope of risk and the technology involved.- Privacy Patterns for Pseudonymity.- Implementing GDPR in the Charity Sector: A Case Study.- Me and My Robot! Sharing Information with a New Friend.- chownIoT: Enhancing IoT Privacy by Automated Handling of Ownership Change.- Is Privacy Controllable?.- Assessing Theories for Research on Personal Data Transparency.- Data Protection by Design for cross-border electronic identication: does the eIDAS Interoperability Framework need to be modernised?.- Risk proling by law enforcement agencies in the Big Data era: Is there a need for transparency?
