1. 25/10/2009Philipp Kärger1 Reactivity and Social Data: Keys to Drive Privacy Decisions in Social Network Applications* * This work was partially supported by the FP7 EU Project OKKAM (contract no. ICT-215032) Philipp Kärger 1, Emily Kigel 1, Daniel Olmedilla 2 1 L3S Research Center 2 Telefonica Research & Development, Madrid, Spain

2. 25/10/2009Philipp Kärger2 Outline 1.Motivation  Privacy settings on the Social Web 2.Background  Semantic Web policies 3.Reactivity and Social Data  Defining Social Concepts in Semantic Web policies  A reactive policy language 4.Implementation 5.Prototype  Reactive Social Web policies in Skype

3. 25/10/2009Philipp Kärger3 Motivation

4. 25/10/2009Philipp Kärger4 How do we make privacy decisions? do I know this guy? did I ever talk to this guy? did I ever meet this guy? is the requested thing private? do I want to share the requested thing?

5. 25/10/2009Philipp Kärger5 Social context?

6. 25/10/2009Philipp Kärger6 … if you are posting in my forum.

7. 25/10/2009Philipp Kärger7 … if you are listening to the same music.

8. 25/10/2009Philipp Kärger8 … if you are working for the same company.

9. 25/10/2009Philipp Kärger9 … if you are participating in the same OpenSource project.

10. 25/10/2009Philipp Kärger10 … if you are in regular email contact with me.

11. 25/10/2009Philipp Kärger11 … if you are my friend on Facebook.

12. 25/10/2009Philipp Kärger12 What is the result of a privacy decision? yes, you can see it but … yes, you can talk to me but only 10 minutes yes, you can call me but not on the mobile phone no, but you can send me an email

13. 25/10/2009Philipp Kärger13 Observations Privacy decisions are not so simple … they depend on the Social context the requester the requested action results are not just “allow/deny” but reactions limited requests

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16. 25/10/2009Philipp Kärger16 Privacy Settings on the Social Web closed world (“walled garden”) what actually influences privacy decisions? static no reaction, just allow and deny no inclusion of strong evidences no inclusion of weak evidences

17. 25/10/2009Philipp Kärger17 Semantic Web Policies

18. 25/10/2009Philipp Kärger18 Semantic Web policies A policy is “a (declarative) description of the behavior of a system”. Semantic Web policies: have a well define semantics incorporate information from difference knowledge sources gained a lot of research effort in the last years several policy frameworks and policy languages are available

19. 25/10/2009Philipp Kärger19 Semantic Web policies - Features Privacy statements can be changed/updated  without re-coding, re-compiling, re-installing, etc.  in a costless manner Reasoning on privacy statements Generation of explanations Reusability Extensibility Context-sensitivity Verifiability

20. 25/10/2009Philipp Kärger20 allow(access(Picture, Requester))  isTagged(Picture,”iswc2009”), isMemberOfGroup(Requester,”iswc2009”). isMemberOfGroup(Person, “iswc2009”)  isMemberInFacebookGroup(Person,“iswc09”). isMemberOfGroup(Person, “iswc2009”)  hasInterest(Person,“Semantic Web”). Semantic Web Policies  incorporating Social Data

21. 25/10/2009Philipp Kärger21 isMemberOfGroup(Person, “iswc2009”)  hasPostedOnMySemWebBlog(Person). isMemberOfGroup(Person, “iswc2009”)  isMyCoAuthor(Person, Conference, Year), Conference = “ISWC”. isMemberOfGroup(Person, “iswc2009”)  providesCredential(Person, Credential), Credential.issuer = “W3C_SemanticWeb_Group”.

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23. 25/10/2009Philipp Kärger23 A Reactive Policy Language

24. 25/10/2009Philipp Kärger24 A Reactive Policy

25. 25/10/2009Philipp Kärger25 Implementation Social Web

26. 25/10/2009Philipp Kärger26 SPoX – Driving the behavior of Skype -S kype Po licy E x tension -Reactive policies define -who is allowed to do what -which notification shows up -Social data can be used as conditions in the policies.

27. 25/10/2009Philipp Kärger27 Defining a reactive policy in SPoX

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29. 25/10/2009Philipp Kärger29 SPOX Don’t miss the Demo at ISWC’s Demo Session Screencast + Downloads at www.L3S.de/~kaerger/SPoX

30. 25/10/2009Philipp Kärger30 Open issues, future work the challenge of identification  matching (identifying properties?)  platform crossing identification (OpenID, FOAF+SSL, keys) integration of other social platforms  which other data is useful for the social context

31. 25/10/2009Philipp Kärger31 Conclusions privacy preferences require social context  social context is available  we exploited it for privacy policies privacy preferences include reactions  such as “you are allowed but only …”  we developed a reactive policy language implementation as extension to Protune application as policy control for Skype