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    Human Factors in Privacy Research

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    Contributor(s)
    Gerber, Nina (editor)
    Stöver, Alina (editor)
    Marky, Karola (editor)
    Language
    English
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    Abstract
    This book covers topics needed to be considered in research around usable privacy. The book starts from a psychological perspective and introduces readers to basic behavioral theories and models that can explain end-user privacy behavior (including the “privacy paradox”) on a theoretical level. Subsequently, an introduction to different study methods (e.g., experiment, survey, interviews, co-creation) used in usable privacy research is given. Based on this, different methodological aspects, such as identifying appropriate questionnaires, and applying User-Centered Design, will be discussed. Finally, the book describes application areas for privacy research such as dark patterns and presents solutions for privacy protection, e.g., regarding consent-giving and PETs. The book aims to bring together the different research approaches to the topic of usable privacy, which often originate from computer science, psychology, and law, and provide a methodologically sound basis for researchers who want to delve deeper into this topic. This is an open access book.
    URI
    https://library.oapen.org/handle/20.500.12657/76226
    Keywords
    Human factors; Human-Machine Interaction; Privacy research; usable privacy; theory of planned behavior; risk-trust model; privacy dimensions; Internet of Things; Dark pattern; privacy enhacing technologies; Human-Computer Studies
    DOI
    10.1007/978-3-031-28643-8
    ISBN
    9783031286438, 9783031286421, 9783031286438
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2023
    Imprint
    Springer International Publishing
    Pages
    380
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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