Human Factors in Privacy Research.

• Author: Gerber, Nina.
• TeilnehmendeR: Stöver, Alina.; Marky, Karola.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2023.; ©2023.
• Year of Publication: 2023
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (380 pages)

Table of Contents

Intro -- Foreword -- Acknowledgements -- About This Book -- Contents -- Part I Theory -- Data Collection Is Not Mostly Harmless: An Introduction to Privacy Theories and Basics -- 1 Introduction -- 2 Privacy Theories -- 2.1 How (Not) to Define Privacy -- 3 Why Do We Need Privacy? -- References -- From the Privacy Calculus to Crossing the Rubicon: An Introduction to Theoretical Models of User Privacy Behavior -- 1 Introduction -- 2 Homo Economicus -- 3 Antecedents → Privacy Concerns → Outcomes (APCO) Model -- 4 Theory of Planned Behavior -- 5 Cognitive Consistency Theories -- 6 Transactional Model of Stress and Coping -- 7 Rubicon Model -- 8 Capability, Opportunity, Motivation → Behavior (COM-B) System -- 9 Health Action Process Approach -- 10 Conclusion -- References -- Part II Methodology -- Empirical Research Methods in Usable Privacy and Security -- 1 Introduction -- 2 Research Methods in UPS Studies -- 2.1 Systematic Literature Reviews -- 2.2 Interviews -- 2.3 Focus Groups -- 2.4 Co-Creation Methods -- 2.5 Surveys -- 2.6 Analyzing Measurement Data (Data Logs) -- 2.7 Extracting Online Datasets -- 2.8 Experience Sampling Method -- 2.9 Experiments -- 3 Techniques that Can Be Used in Combination with Methods -- 4 Participant Recruitment -- 5 Basics of Ethical Research Design with Human Participants -- 5.1 Ethical Core Principles -- 5.2 Ethical Considerations for Deceptive Research -- 5.3 Ethical Review Boards -- 6 Biases in Research with Human Participants -- 7 Conclusion -- References -- Toward Valid and Reliable Privacy Concern Scales: The Example of IUIPC-8 -- 1 Introduction -- 2 Information Privacy Concern -- 2.1 What Is Information Privacy Concern? -- 2.2 Information Privacy Concern Instruments -- 3 Validity and Reliability -- 3.1 Construct Validity -- 3.2 Reliability -- 4 Factor Analysis as Tool to Establish Measurement Instruments.

4.1 Estimation Methods for Ordinal Non-normal Data -- 4.2 Comparing Nested Models -- 4.3 Global and Local Fit -- 5 Approach -- 5.1 Analysis Methodology -- 5.2 Sample -- 5.3 Validity and Reliability Criteria -- 6 The Validation of IUIPC-8 -- 6.1 Sample -- 6.2 Descriptives -- 6.3 Construct Validity -- Factorial Validity -- Model Fit -- CFA Model, Convergent, and Discriminant Validity -- 6.4 Reliability: Internal Consistency -- 7 Discussion -- 8 Summary -- Appendix -- Materials and Sample -- Thresholds -- References -- Achieving Usable Security and Privacy Through Human-Centered Design -- 1 Introduction -- 2 Background -- 2.1 Human-Centered Design -- 2.2 Usable Security and Privacy -- 3 Mental Models in Security and Privacy -- 3.1 Mental Models in Human-Computer Interaction -- 3.2 Mental Models in Usable Security and Privacy -- 3.3 Mental Model Elicitation -- 4 Usable Security and Privacy Needs -- 4.1 USP Needs as a Requirements Type -- 4.2 USP Needs Elicitation and Analysis -- 4.3 USP Needs Documentation and Validation -- 4.4 Example Case Study -- 5 User Group Profiles and Privacy Personas -- 5.1 User Group Profiles -- 5.2 Privacy Personas -- 6 Summary and Conclusion -- References -- What HCI Can Do for (Data Protection) Law-Beyond Design -- 1 Introduction -- 2 The Call for Effective Measures: A Door Opener for Empirical Sciences -- 3 Going Beyond Designing Law: The Case for the Full Toolbox of HCI Research -- 4 Levels of Engagement: How HCI and Law Can Make Data Protection More Effective -- 4.1 Case 1: Cookie Banners -- 4.2 Case 2: Data Subject Rights -- 4.3 Implementation: What Can Design Do for Law? -- 4.4 Evaluation: How Well Is Law Currently Working? -- 4.5 Identification: Challenging Existing Legal Interpretations and Concepts -- 5 The Road Ahead -- References -- Expert Opinions as a Method of Validating Ideas: Applied to Making GDPR Usable.

1 Introduction -- 2 Method -- 2.1 Collecting Interview Data -- 2.2 Participants -- 2.3 Thematic Analysis -- 3 The Need to Evaluate and Measure Usability of Privacy -- 3.1 Evaluating Usability of Privacy -- 3.2 Measuring Usability of Privacy -- 4 Usable Privacy Definition Adapts Well ISO 9241-11:2018 -- 5 A Comprehensive List of Usable Privacy Goals -- 6 Ways to Meet the Usable Privacy Criteria -- 7 Usable Privacy Cube Model as an Abstraction of Known and Implied Principles of Privacy Evaluations -- 8 Summarizing the Results of the Validation Study -- 9 Conclusion -- References -- Part III Application Areas -- Privacy Nudges and Informed Consent? Challenges for Privacy Nudge Design -- 1 Introduction to Nudging -- 2 An Overview on Privacy Nudges -- 3 Ethical Considerations -- 4 Challenges of Designing Privacy Nudges -- 5 Discussion of Approaches -- 5.1 Design of Privacy-Preserving Nudges -- 5.2 Design of Nudges that Target Reflective Thinking -- 5.3 Ask the Users -- 5.4 Choose a Combination of Approaches -- 6 Summary -- References -- The Hows and Whys of Dark Patterns: Categorizations and Privacy -- 1 Introduction -- 2 Dark Patterns -- 2.1 Why Do Dark Patterns Work? -- Heuristics and Biases -- 2.2 Privacy Decision-Making -- 2.3 Categorization of Dark Patterns -- 3 Privacy Dark Patterns -- 3.1 Examples of Privacy Dark Patterns -- Invisible to the Human Eye -- UI Design Tricks -- Constrained Actionability -- Emotion-Related -- Affecting Comprehension -- Time-Related -- Affecting Privacy Options -- 3.2 Tackling (Privacy) Dark Patterns -- 3.3 Dark Patterns and Implications on Businesses -- 4 Concluding Remarks -- References -- ``They see me scrollin''-Lessons Learned from Investigating Shoulder Surfing Behavior and Attack Mitigation Strategies -- 1 Introduction -- 2 Investigating the Phenomenon -- 2.1 Defining Shoulder Surfing (Attacks).

2.2 Research Methods -- 2.3 Key Findings on Shoulder Surfing Behavior -- 3 Mitigating Shoulder Surfing Attacks -- 3.1 Threat Models -- 3.2 Algorithmic Detection of Attacks -- 3.3 Prevention Strategies -- 4 Challenges and Future Research Directions -- 5 Conclusion -- References -- Privacy Research on the Pulse of Time: COVID-19 Contact-Tracing Apps -- 1 Introduction -- 2 Tracing Technologies -- 2.1 Proximity Tracing -- 2.2 Risk Calculation and Informing Those at Risk -- 3 Privacy and Contact Tracing Apps-User Studies -- 3.1 Results from User Studies-Privacy Concerns -- 3.2 Influence of Privacy on Using a CTA -- 4 Privacy: A Matter of Asking? Looking at Different Methods -- 4.1 Timing and Context -- 4.2 Who Is Asked? -- 4.3 Privacy Concerns != Privacy Concerns -- 5 Conclusion -- References -- Privacy Perception and Behavior in Safety-Critical Environments -- 1 Introduction -- 2 On the Relationship Between Cyber Privacy and Security Behavior -- 3 Awareness on Data Sharing Functionalities and Acceptance of Private Data Sharing -- 4 Critical Environment I: Digital Privacy Perceptions of Asylum Seekers in Germany -- 5 Critical Environment II: The Role of Privacy in Digitalization-Analyzing Perspectives of German Farmers -- 6 Conclusion -- References -- Part IV Solutions -- Generic Consents in Digital Ecosystems: Legal, Psychological, and Technical Perspectives -- 1 Challenge and Vision -- 2 Generic Consents -- 3 Legal Assessment -- 3.1 Personal Information Management Systems in Digital Ecosystems -- 3.2 Obtaining Consent via a PIMS -- 3.3 Using Allowlists in Digital Ecosystems -- Solution 1: Organizational Allowlists -- Solution 2: User-Defined Allowlists -- 3.4 Legal Conclusion -- 4 User-Oriented Redesign of Consent Handling -- 4.1 Psychological Effects of Cookie Banners -- Problem 1: Upfront Consents -- Problem 2: Coerced Consents.

Problem 3: Poor User Experience -- Problem 4: Unclear Utility -- Problem 5: Dark Patterns -- Problem 6: Repeated Consents -- 4.2 Solutions for Improved User Experience -- Solution 1: Make Cookies Something of Later Concern -- Solution 2: Reject Until Further Notice -- Solution 3: Provide Differentiated Decision Support -- Solution 4: Encourage Decision Review -- 5 Feasibility of Technical Implementation -- 5.1 Consent Representation Formats -- 5.2 Consent Forwarding -- 5.3 Data Forwarding -- 6 Discussion -- 6.1 Allowlists Created by NGOs (Solution 1) -- 6.2 Allowlists Created by the User (Solution 2) -- 6.3 Blocklists -- 6.4 Usability -- 7 Conclusion -- References -- Human-Centered Design for Data-Sparse Tailored Privacy Information Provision -- 1 Motivation -- 2 Overview of Extant Transparency-Enhancing Technologies -- 2.1 Tailoring Potential of Transparency-Enhancing Technologies -- 3 Solution Space for Tailoring Challenges -- 3.1 Privacy Preferences -- 3.2 Technical Privacy-Preserving Mechanisms -- 4 Solution Archetypes for Tailored Privacy Information Provision -- 4.1 Suitability of Tailoring Approaches -- 4.2 Feasibility of Local and Remote Processing -- 5 Conclusions -- References -- Acceptance Factors of Privacy-Enhancing Technologies on the Basis of Tor and JonDonym -- 1 Introduction and Background -- 2 Methodology -- 2.1 Questionnaire Composition -- 2.2 Questionnaire Data Collection -- 2.3 Questionnaire Evaluation -- Quantitative Methods -- Qualitative Methods -- 2.4 Interview Data Collection -- 2.5 Interview Evaluation -- 3 Results -- 3.1 Internet Users Information Privacy Concerns -- 3.2 Technology Acceptance Model -- 3.3 Evaluation of Open Questions -- 3.4 Customers' Willingness to Pay or Donate -- 3.5 Companies' Incentives and Hindrances to Implement PETs -- 4 Discussion and Conclusion -- References.

Increasing Users' Privacy Awareness in the Internet of Things: Design Space and Sample Scenarios.