1. K.U.Leuven George Danezis 1, Markulf Kohlweiss 1, Ben Livshits 1, and Alfredo Rial 2 Private Client-Side Profiling with Random Forests and Hidden Markov Models 1 Microsoft Research 2 KU Leuven ESAT/COSIC – IBBT, Belgium PETS 2012 Private Client-Side ProfilingPETS 2012

2. Introduction System Overview Applications Random Forests Our Protocol Conclusion Index 2Private Client-Side Profiling http://www.dmrdirect.com/direct-mail/customer-profiling/gain-valuable-marketing-intelligence/

3. PETS 2012 1 – Introduction 3Private Client-Side Profiling http://blog.maia-intelligence.com/2009/10/05/customer-analytics-in-retail/

4. PETS 2012 Client Profiling -> Deliver Customized Services Current techniques: o Cookies o Third party apps in social networks o Web bugs Disadvantages o Privacy o Correctness Ad-hoc Block Current Client Profiling Tools 4Private Client-Side Profiling http://www.pc-xp.com/2010/12/04/web-bug-reveals-internet-browsing-history/

5. PETS 2012 User’s perform the classification task: o Input certified features and certified algorithm o Run algorithm: Classification: Random Forest Pattern Recognition: Hidden Markov Model o Output result and proof of correctness o Service provider verifies result Advantages o Privacy: Only classification result is disclosed o Correctness guaranteed by proof Private Client-Side Profiling 5

6. PETS 2012 2- System Overview 6Private Client-Side Profiling

7. PETS 2012 Behavioral advertising P2P dating & matchmaking Financial logs Pay-as-you-drive Insurance Bio-medical & genetic 3- Applications 7Private Client-Side Profiling

8. PETS 2012 Behavioural Advertising 8Private Client-Side Profiling http://kickstand.typepad.com/metamuse/2008/05/behavioral-adve.html

9. PETS 2012 P2P Dating & Matchmaking 9Private Client-Side Profiling http://www.robhelsby.com/P2P%20Dating.html

10. PETS 2012 Financial logs 10Private Client-Side Profiling http://www.ikeepsafe.org/privacy/arm-yourself-against-online-fraud/

11. PETS 2012 Pay-as-you-drive Insurance 11Private Client-Side Profiling http://www.fenderbender.com/FenderBender/April-2011/Pay-As-You-Drive-Insurance/

12. PETS 2012 Bio-medical & Genetic 12Private Client-Side Profiling http://www.pattern-expert.com/Bioinformatics/eng/bioinformatics/SNPAnalysis.html

13. PETS 2012 4- Random Forests 13Private Client-Side Profiling http://www.iis.ee.ic.ac.uk/~tkkim/iccv09_tutorial.html

14. PETS 2012 Definition of Random Forest 14Private Client-Side Profiling

15. PETS 2012 Tree Example 15Private Client-Side Profiling

16. PETS 2012 Zero-Knowledge Proofs of Knowledge P-Signatures: signature schemes with an efficient ZKPK of signature possession 5- Our Protocol 16Private Client-Side Profiling

17. PETS 2012 LOOKUP ZKTABLE Notation 17Private Client-Side Profiling

18. PETS 2012 A sends Prover his certified features: Phase 1 18Private Client-Side Profiling

19. PETS 2012 A’ sends Prover a certified random forest: Branches: o Left Branches: o Right Branches: Leaf nodes: Phase 2 19Private Client-Side Profiling

20. PETS 2012 Prover computes the following ZKPK: Phase 3 – Tree Resolution 20Private Client-Side Profiling

21. PETS 2012 Prover repeats tree resolution for all the trees Phase 3 – Forest Resolution 21Private Client-Side Profiling

22. PETS 2012 P-signature scheme by Au et al. [SCN 2006] Hidden range proof based on Camenisch et al. [Asiacrypt 2008] Random forest parameters: o Number of trees: t = 50 o Depth: D = 10 o Number of features: M = 100 o Average number of feature values: K = 100 Instantiation 22Private Client-Side Profiling

23. PETS 2012 F u = Table of certified user features B t = Table of branches of all trees L t = Table of leaf nodes of all trees V t = Table of signatures for the hidden range proof P t = Proof of random forest resolution Efficiency 23Private Client-Side Profiling

24. PETS 2012 Private Client-Side Profiling: o Classification: Random Forests o Pattern Recognition: Hidden Markov Models The mere act of profiling may violate privacy. Conclusion 24Private Client-Side Profiling “We do not see the power which is in speech because we forget that all speech is a classification, and that All classifications are oppressive” Roland Barthes

25. PETS 2012 Comparison Shopping 25Private Client-Side Profiling http://article.wn.com/view/2012/04/19/Life_insurance_cos_new_biz_premiums_down_92/