Web Privacy with P3p

By Lorrie Faith Cranor, Lawrence Lessig. 2002

311 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/7ac72dc9a5d7a49be3f0c772ebe04dccdf1916d7

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Citations in the corpus

The Effect of Online Privacy Information on Purchasing Behavior: An Experimental Study (2011, methodology): “People use software tools to define their privacy preferences and determine if websites’ P3P privacy policies match those preferences (Cranor, 2002).”
Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence (2020, methodology): “The Platform for Privacy Preferences (P3P) was an involved attempt to help automate some of this process by building a machine-readable language for expressing website privacy policies which could then interface with user agents, such as the browser or other privacy applications [19].”
Engineering Privacy (2009, background): “Discussions of how to create usable privacy policies are covered elsewhere [102], [103].”
Privacy and contextual integrity: framework and applications (2006, methodology): “A number of frameworks for defining and enforcing access control and privacy policies have been proposed, including RBAC [12, 14, 25], EPAL [7, 8, 38], and P3P [1, 2, 13, 15, 16, 34].”
Taking account of privacy when designing cloud computing services (2009, background): “• privacy management tools that enable inspection of service-side polices about the handling of personal data (for example, software that allows browsers to automatically detect the privacy policy of websites and compare it to the preferences expressed by the user, highlighting any clashes [19,20,21”
Standardizing privacy notices: an online study of the nutrition label approach (2010, methodology): “The tabular format can be filled in automatically if a site uses a W3C protocol called the Platform for Privacy Preferences (P3P) [15, 2].”
Personal information management (2004, background): “And we might even hope that the policy could travel with the information as it is transferred (Cranor, 2002).”
Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning (2018, background): “Several proposals have aimed at alternative methods and UIs for presenting privacy notices [8], including machine-readable formats [13], nutrition labels [14], privacy icons (recently recommended by the EU [15]), and short notices [16].”
User interfaces for privacy agents (2006, methodology): “5 Chapter 11 of Web Privacy With P3P [13] discusses the rationale behind some of the P3P vocabulary design decisions in more detail.”