The Platform for Privacy Preferences Project Lorrie Faith

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The Platform for Privacy Preferences Project Lorrie Faith Cranor AT&T Labs-Research Co-Chair, P 3

The Platform for Privacy Preferences Project Lorrie Faith Cranor AT&T Labs-Research Co-Chair, P 3 P Interest Group http: //www. research. att. com/~lorrie/ http: //www. w 3. org/P 3 P/

Empowerment Tools n Prevent your actions from being linked to you Crowds - AT&T

Empowerment Tools n Prevent your actions from being linked to you Crowds - AT&T Labs n Allow you to develop persistent relationships not linked to each other or you Lucent Personal Web Assistant - Bell Labs n Make informed choices about how your information will be used Platform for Privacy Preferences Project - W 3 C n Know that assurances about information practices are trust worthy TRUSTe - Electronic Frontier Foundation and Commerce. Net 2

Platform for Privacy Preferences Project (P 3 P) A framework for automated privacy discussions

Platform for Privacy Preferences Project (P 3 P) A framework for automated privacy discussions under development by W 3 C l Services communicate about practices l Users exercise preferences over those practices l User agent can facilitate automated decision making, prompt user, exchange data, etc. 3

Basic P 3 P Concepts proposal user agent service agreement user data repository preferences

Basic P 3 P Concepts proposal user agent service agreement user data repository preferences data practices 4

A Simple P 3 P Conversation service user agent User agent: Get index. html

A Simple P 3 P Conversation service user agent User agent: Get index. html Service: Here is my P 3 P proposal - I collect click-stream data and computer information for web site and system administration and customization of site User agent: OK, I accept your proposal Service: Here is index. html 5

More Complicated Conversations n Service offers choice of proposals n User agent makes counter

More Complicated Conversations n Service offers choice of proposals n User agent makes counter proposal n User agent rejects proposal and asks service for another offer n Upon agreement, user agent automatically sends requested data n No agreement is reached 6

Where we are and where we’re going. . . n Overall architecture n Proposal

Where we are and where we’re going. . . n Overall architecture n Proposal grammar October 1997 n Harmonized vocabulary n Protocol structure March 1998 n Syntax (encoded in RDF or XML) May 1998? n Implementation guide n Preference interchange language 7

P 3 P Grammar n Experience space n Qualified data set n Service provider’s

P 3 P Grammar n Experience space n Qualified data set n Service provider’s identity l data set/element l data category n URL for privacy policy n Consequence n Purpose n Qualifiers n Required 8

P 3 P Vocabulary n Purpose n Data category n Qualifiers l identifiable use

P 3 P Vocabulary n Purpose n Data category n Qualifiers l identifiable use l recipients (domain of use) l general disclosures «access to identifiable information «assurance (accountability) «other disclosures • change agreement • retention 9

Data Categories n Physical contact information n Navigation and click-stream data n Online contact

Data Categories n Physical contact information n Navigation and click-stream data n Online contact information n Transaction data n Unique identifiers n Financial account identifiers n Computer information n Demographic and socio-economic data n Preference data n Content 10

Purposes n Completion and support of current activity n Web site and system administration

Purposes n Completion and support of current activity n Web site and system administration n Customization of site to individuals n Research and development n Contacting visitors for marketing of services or products n Other uses 11

Implementation Guide n Guiding principles n Guidelines for user agent implementers n Guidelines for

Implementation Guide n Guiding principles n Guidelines for user agent implementers n Guidelines for service providers n Guidelines for server implementers n Guidelines for creators of recommended settings n Guidelines for users 12

Guiding Principles n Information Privacy n Notice n Choice and Control n Fairness and

Guiding Principles n Information Privacy n Notice n Choice and Control n Fairness and Integrity n Security 13

Keys to Success n Good end-user implementations l easy to use «easy to plug

Keys to Success n Good end-user implementations l easy to use «easy to plug in “recommended settings” «not annoying l use incremental adoption model l privacy friendly n Good server implementations and tools n Adoption by many Web sites n Users find it useful n Endorsement by governmentregulatory and selfregulatory organizations 14