This work considers the privacy attributes mapped by the work of Barth, Ionita, and Hartel [1], summarised in the listing bellow.
Accountability
Accountability refers to holding the service provider responsible for any violations of privacy policies, including ensuring that their practices comply with legal standards and regulations.
Accountability is related to the following guidelines:
Anonymisation
Anonymisation involves removing all identifiable markers from data so that it cannot be traced back to an individual, ensuring that personal information is irreversibly obscured.
Anonymisation currently has no related guidelines.
Collection
Involves identifying the types of data collected, such as IP addresses, phone numbers, and credit card information. It distinguishes between personally identifiable information and anonymous data and emphasises data minimisation by collecting only necessary data for service provision
Collection is related to the following guidelines:
- Enable Exploration of Data Exports
- Enhance Privacy Policy Communication with Automated Information Extraction
- Leverage Personalised Recommendations for Enhanced User Management of Privacy Settings
- Enhance Parental Control in Smart Toys
- Implement Interactive Consent Forms for Enhanced User Engagement
Control
The key aspects of control are consent, opt-out options, self-determination, influence over data handling, and user-friendly privacy settings.
Control is the main privacy attribute of the following guidelines:
- Encourage Users to Consider Privacy Implications Before Sharing Online
- Implement Contextual Privacy Controls for Enhanced User Data Protection
- Implement Collaborative Privacy Management for Shared Data in Social Networks
- Encourage the Consideration of Interdependent Privacy Management in Cloud Applications
- Enhance Parental Control in Smart Toys
- Explore Diverse Techniques for Privacy Control
- Implement Interactive Privacy Policy Interfaces
- Integrate Automated Tools and Custom Options for Privacy Settings
- Enhance User Privacy Controls in Mobile Applications
- Leverage Personalised Recommendations for Enhanced User Management of Privacy Settings
- Provide Users with User-Friendly Tools to Manage Their Privacy Settings
- Implement Interactive Consent Forms for Enhanced User Engagement
- Leverage Automated Decision-Making for Enhanced User Privacy Controls in Mobile Applications
- Implement Integrated Personal Data Storage to Allow Users to Store and Manage Their Personal Data
- Enhance Collaborative Privacy Management in Photo Sharing
Control is also related to the following guidelines:
- Communicate Privacy Risk with Colour-Coded Privacy Indicators
- Implement User-Customisable Multi-View Privacy Notifications
- Incorporate Icons to Improve Privacy Policy Communication
- Integrate Privacy Indicators for Informed App Selection
- Enable Exploration of Data Exports
- Promote User Awareness and Decision-Making on Permission/Authorisation Requests
- Implement Visual Strategies for Effective Communication of Lengthy Privacy Policies
- Enhance Privacy Policy Communication with Automated Information Extraction
- Enhance Privacy Policy Communication through Assessment Tools
- Enhance Privacy Awareness by Communicating Privacy Risks
- Support the Visualisation and Comprehension of Disclosed Data
Correctness
Correctness involves correcting incorrect or no longer valid data after it has been disclosed, ensuring that it remains accurate and up-to-date.
Correctness is related to the following guidelines:
Functionality
Addresses the balance between privacy and the utility of a service, ensuring users are not forced to choose between maintaining their privacy and accessing a service's full capabilities. It involves designing systems that don't restrict features or services unless personal data is provided, thereby preventing artificial limitations that could coerce users into sharing more personal information than they are comfortable with for full functionality.
Functionality is related to the following guidelines:
Pseudonymisation
Pseudonymisation refers to replacing personal identifiers in data with artificial identifiers or pseudonyms, allowing data to be matched with individuals only when combined with additional information, thereby reducing the risk of privacy breaches while maintaining data utility.
Pseudonymisation is related to the following guidelines:
Purpose
Collected data can be used for purposes such as service provision, advertising, and profiling. Also considers the legal basis for data processing, including legal requirements or vital/public interest.
Purpose is related to the following guidelines:
Retention
How long is the collected data stored? This attribute addresses the duration of data storage to ensure that data are not kept longer than necessary.
Retention is related to the following guidelines:
Right to be forgotten
Refers to allowing individuals to request the deletion or removal of their personal data.
Right to be forgotten currently has no related guidelines.
Sale
Refers to selling personal data to third parties for commercial gain.
Sale currently has no related guidelines.
Security
The security attribute focuses on the technical measures to protect data from unauthorised or malicious access, ensuring that personal information is safeguarded against potential breaches or cyber threats.
Security is related to the following guidelines:
- Implement Integrated Personal Data Storage to Allow Users to Store and Manage Their Personal Data
- Integrate Automated Tools and Custom Options for Privacy Settings
- Leverage Automated Decision-Making for Enhanced User Privacy Controls in Mobile Applications
- Provide Users with User-Friendly Tools to Manage Their Privacy Settings
- Leverage Personalised Recommendations for Enhanced User Management of Privacy Settings
Sharing
The sharing attribute refers to whether and how collected data is shared with third parties without monetary compensation. This includes sharing data with other companies, advertisers, research institutions, and other external entities. Sharing can encompass both voluntary and unintentional disclosures.
Sharing is related to the following guidelines:
Transparency
The ability users have to access information about how their personal data is handled, including through open-source code, privacy policies, and regular audits. Also involves proactive distribution of information to users, demonstrating the implementation of privacy attributes to data subjects and regulators.
Transparency is the main privacy attribute of the following guidelines:
- Enhance Privacy Policy Communication through Assessment Tools
- Communicate Privacy Risk with Colour-Coded Privacy Indicators
- Enhance Privacy Awareness by Communicating Privacy Risks
- Implement User-Customisable Multi-View Privacy Notifications
- Promote User Awareness and Decision-Making on Permission/Authorisation Requests
- Implement Visual Strategies for Effective Communication of Lengthy Privacy Policies
- Incorporate Icons to Improve Privacy Policy Communication
- Enable Exploration of Data Exports
- Support the Visualisation and Comprehension of Disclosed Data
- Integrate Privacy Indicators for Informed App Selection
- Enhance Privacy Policy Communication with Automated Information Extraction
Transparency is also related to the following guidelines:
- Implement Interactive Privacy Policy Interfaces
- Implement Contextual Privacy Controls for Enhanced User Data Protection
- Encourage Users to Consider Privacy Implications Before Sharing Online
- Enhance User Privacy Controls in Mobile Applications
- Encourage the Consideration of Interdependent Privacy Management in Cloud Applications
- Leverage Automated Decision-Making for Enhanced User Privacy Controls in Mobile Applications
- Integrate Automated Tools and Custom Options for Privacy Settings
- Enhance Parental Control in Smart Toys
- Provide Users with User-Friendly Tools to Manage Their Privacy Settings
- Leverage Personalised Recommendations for Enhanced User Management of Privacy Settings
- Explore Diverse Techniques for Privacy Control
- Implement Interactive Consent Forms for Enhanced User Engagement