By Claude Castelluccia, Mohamed-Ali Kaafar, Minh-Dung Tran (auth.), Simone Fischer-Hübner, Matthew Wright (eds.)
This publication constitutes the refereed lawsuits of the 12 th overseas Symposium on privateness improving applied sciences, puppy 2012, held in Vigo, Spain, in July 2012. The sixteen complete papers offered have been conscientiously chosen from seventy two submissions. subject matters addressed comprise anonymization of information, content material, and site visitors, community site visitors research, censorship-resistant structures, consumer profiling, education clients in privateness possibility administration, and privateness of web and cloud-bases providers. yet another spotlight is the HotPETS consultation, designed as a venue to offer latest yet nonetheless initial and evolving ideas.
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Extra resources for Privacy Enhancing Technologies: 12th International Symposium, PETS 2012, Vigo, Spain, July 11-13, 2012. Proceedings
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Ltering of the users with respect to criteria such as music tastes or hair color, would be done locally, on each of the P2P nodes. ” We can prevent this by requiring users to commit to their preferences and attributes at most once, and then use the same, committed, profile when answering matching queries from different parties. In this scenario, trust is rooted in the fact that users cannot have their attributes certified at will, and can only do so in a restricted manner: either through 22 G. Danezis et al.
Ti , si , ei , pi , pi , p : (21) e0 , u = LOOKUPSu (t0 ) ∧ p0 = LOOKUPIt (s0 ) ∧ (22) (23) p0 = LOOKUPEt (s0 , e0 ) ∧ for i = 1 . . |i| − 1 : { (24) (25) ti = t0 + i ∧ ei , u = LOOKUPSu (ti ) ∧ (26) (27) pi = LOOKUPTt (si−1 , si ) ∧ pi = LOOKUPEt (si , ei )} ∧ (28) (29) l−1 (pi + pi ) ∧ p= (30) 0 POpenCp (p, open p ) ∧ POpenCs l−1 (sl−1 , open sl−1 ) (31) The main result of the protocol is a commitment Csl−1 to the final state sl−1 and a commitment Cp to the probability p of reaching this state.
Towards ensuring client-side computational integrity. , Ristenpart, T. ) CCSW, pp. 125–130. ACM (2011) 24. : Gene selection and classification of microarray data using random forest. BMC Bioinformatics 7(1), 3 (2006) 25. : How to Prove Yourself: Practical Solutions to Identification and Signature Problems. M. ) CRYPTO 1986. LNCS, vol. 263, pp. 186–194. Springer, Heidelberg (1987) 26. : Repriv: Re-imagining content personalization and inbrowser privacy. In: IEEE Symposium on Security and Privacy, pp.