Towards a broadening of privacy decision-making models: The use of cognitive architectures

Yefim Shulman*

*Corresponding author for this work

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

2 Citations (Scopus)

Abstract

Over the last decades, people’s behaviour and attitudes towards privacy have been thoroughly studied by scholars, approaching the issue from different perspectives. To address privacy-related decisions, it is necessary to consider aspects of human cognition, employing, for instance, methods used in Human-Computer Interaction and Information Science research. This paper analyses findings and contributions of existing privacy decision-making research, and suggests filling gaps in current understanding by applying a cognitive architecture framework to model privacy decision-making. This may broaden the range of factors and their relationships that can be integrated into the models of privacy decisions, beyond those in existing decision models.

Original languageEnglish
Title of host publicationPrivacy and Identity Management. The Smart Revolution - 12th IFIP WG 9.2, 9.5, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School, Revised Selected Papers
EditorsIgor Nai-Fovino, Marit Hansen, Eleni Kosta, Simone Fischer-Hubner
PublisherSpringer New York
Pages187-204
Number of pages18
ISBN (Print)9783319929248
DOIs
Publication statusPublished - 2018
Event12th Annual IFIP Summer School on Privacy and Identity Management, 2017 - Ispra, Italy
Duration: 4 Sept 20178 Sept 2017

Publication series

SeriesIFIP Advances in Information and Communication Technology
Volume526
ISSN1868-4238

Conference

Conference12th Annual IFIP Summer School on Privacy and Identity Management, 2017
Country/TerritoryItaly
CityIspra
Period4/09/178/09/17

Bibliographical note

Funding Information:
I gratefully acknowledge the suggestions from my Ph.D. advisor, Professor Joachim Meyer. This paper is a part of the author’s Ph.D. research on “Modelling Responses to Privacy-related Indications”. The research is conducted under and supported by the Privacy & Us innovative training network (EU H2020 MSCA ITN, grant agreement №675730).

Funding Information:
This paper is a part of the author’s Ph.D. research on “Modelling Responses to Privacy-related Indications”. The research is conducted under and supported by the Privacy & Us innovative training network (EU H2020 MSCA ITN, grant agreement №675730).

Publisher Copyright:
© IFIP International Federation for Information Processing 2018.

Research programs

  • ESSB PSY

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