Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11565))

  • 425 Accesses

Abstract

Security protocols enable secure communication over insecure channels. Privacy protocols enable private interactions over secure channels. Security protocols set up secure channels using cryptographic primitives. Privacy protocols set up private channels using secure channels. But just like some security protocols can be broken without breaking the underlying cryptography, some privacy protocols can be broken without breaking the underlying security. Such privacy attacks have been used to leverage e-commerce against targeted advertising from the outset; but their depth and scope became apparent only with the overwhelming advent of influence campaigns in politics. The blurred boundaries between privacy protocols and privacy attacks present a new challenge for protocol analysis. Or maybe they do not, as the novelty is often in the eye of the observer. Cathy Meadows spearheaded and steered our research in security protocols. The methods for analyzing privacy protocols arise directly from her work.

J. Castiglione—Supported by NSF.

D. Pavlovic—Partially supported by NSF and AFOSR.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Information is, of course, a resource, so it can be private.

  2. 2.

    A \(\mathcal{Y}\times \mathcal{Y}\)-matrix with finitely many nonzero, nonnegative entries is doubly stochastic if the sums of the entries in each nonzero row and in each nonzero column are 1. Already Garrett Birkhoff considered infinite doubly stochastic matrices, asking for the infinitary generalization of his doubly stochastic decomposition in the problem 111 of his Lattice Theory.

  3. 3.

    Nikolai Vasilievich Gogol was a XIX century Russian writer. Gogols are also the ape-like enemies in the video game Xenoblade Chronicles.

  4. 4.

    Gogol receives advertising requests in a separate privacy protocol. It will be briefly discussed in the next section.

References

  1. Acquisti, A., Gritzalis, S., Lambrinoudakis, C., di Vimercati, S.: Digital Privacy: Theory, Technologies, and Practices. CRC Press, Boca Raton (2007)

    Google Scholar 

  2. Alberti, P.M., Uhlmann, A.: Stochasticity and Partial Order: Double Stochastic Maps and Unitary Mixing. Mathematics and its Applications. Springer, Heidelberg (1981)

    MATH  Google Scholar 

  3. Ando, T.: Majorization, doubly stochastic matrices, and comparison of eigenvalues. Linear Algebra Appl. 118, 163–248 (1989)

    Article  MathSciNet  Google Scholar 

  4. Angela, A., Conti, G.: A Day in the Life of Ancient Rome. Europa Editions, New York (2009)

    Google Scholar 

  5. Angwin, J.: Dragnet Nation: A Quest for Privacy, Security, and Freedom in a World of Relentless Surveillance. Henry Holt and Company, New York (2014)

    Google Scholar 

  6. Arendt, H.: The Human Condition. Charles R. Walgreen Foundation Lectures, Second edn. University of Chicago Press, Chicago (1998)

    Google Scholar 

  7. Bailey, J.: From public to private: the development of the concept of “private”. Soc. Res. 69(1), 15–31 (2002)

    MathSciNet  Google Scholar 

  8. Ball, K., Haggerty, K., Lyon, D.: Routledge Handbook of Surveillance Studies. Routledge International Handbooks. Taylor & Francis, Milton Park (2012)

    Google Scholar 

  9. Benkler, Y.: The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press, New Haven (2006)

    Google Scholar 

  10. Birkhoff, G.: Tres observaciones sobre el algebra lineal. Univ. Nac. Tucumán Rev. Ser. A 5, 147–151 (1946)

    Google Scholar 

  11. Brandt, F., Conitzer, V., Endriss, U., Lang, J., Procaccia, A.D.: Handbook of Computational Social Choice. Cambridge University Press, Cambridge (2016)

    Google Scholar 

  12. Burke, S.: Delos: investigating the notion of privacy within the ancient greek house. Ph.D. thesis, University of Leicester (2000)

    Google Scholar 

  13. Cervesato, I., Meadows, C., Pavlovic, D.: An encapsulated authentication logic for reasoning about key distribution protocols. In: Guttman, J. (ed.) Proceedings of CSFW 2005, pp. 48–61. IEEE (2005)

    Google Scholar 

  14. Dalenius, T.: Towards a methodology for statistical disclosure control. Statistik Tidskrift 15, 429–444 (1977)

    Google Scholar 

  15. Datta, A., Derek, A., Mitchell, J., Pavlovic, D.: A derivation system and compositional logic for security protocols. J. Comput. Secur. 13, 423–482 (2005)

    Article  Google Scholar 

  16. Datta, A., Derek, A., Mitchell, J.C., Pavlovic, D.: Abstraction and refinement in protocol derivation. In: Focardi, R. (ed.) Proceedings of CSFW 2004, pp. 30–47. IEEE (2004)

    Google Scholar 

  17. Diffie, W., Landau, S.: Privacy on the Line: The Politics of Wiretapping and Encryption. MIT Press, Cambridge (2010)

    Google Scholar 

  18. van Dijk, J.: The Network Society. SAGE Publications, Thousand Oaks (2012)

    Google Scholar 

  19. Durgin, N., Mitchell, J., Pavlovic, D.: A compositional logic for proving security properties of protocols. J. Comput. Security 11(4), 677–721 (2004)

    Article  Google Scholar 

  20. Yearwood, M.H., et al.: On wealth and the diversity of friendships: high social class people around the world have fewer international friends. Personality Individ. Differ. 87, 224–229 (2015)

    Article  Google Scholar 

  21. Habermas, J.: The Structural Transformation of the Public Sphere: An Inquiry into a Category of Bourgeois Society. Studies in Contemporary German Social Thought. MIT Press, Cambridge (1991)

    Google Scholar 

  22. Hardy, G.H., Littlewood, J.E., Pólya, G.: Inequalities. The University Press (1934)

    Google Scholar 

  23. Kosinski, M., Stillwell, D., Graepel, T.: Private traits and attributes are predictable from digital records of human behavior. Proc. Natl. Acad. Sci. 110(15), 5802–5805 (2013)

    Article  Google Scholar 

  24. Malin, B., Sweeney, L.: Re-identification of DNA through an automated linkage process. In: American Medical Informatics Association Annual Symposium, AMIA 2001, Washington, DC, USA, 3–7 November 2001. AMIA (2001)

    Google Scholar 

  25. Marshall, A.W., Olkin, I.: Inequalities: Theory of Majorization and Its Applications. Mathematics in Science and Engineering, vol. 143. Academic Press, Cambridge (1979)

    Google Scholar 

  26. Meadows, C., Pavlovic, D.: Deriving, attacking and defending the GDOI protocol. In: Samarati, P., Ryan, P., Gollmann, D., Molva, R. (eds.) ESORICS 2004. LNCS, vol. 3193, pp. 53–72. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30108-0_4

    Chapter  Google Scholar 

  27. Narayanan, A., Shmatikov, V.: Robust de-anonymization of large sparse datasets. In: Proceedings of the 2008 IEEE Symposium on Security and Privacy, SP 2008, pp. 111–125. IEEE Computer Society, Washington (2008)

    Google Scholar 

  28. Nielsen, M.A.: Characterizing mixing and measurement in quantum mechanics. Phys. Rev. A 63(2), 022114 (2001)

    Google Scholar 

  29. Orlin, L.C.: Locating Privacy in Tudor London. Oxford University Press, Oxford (2009)

    Google Scholar 

  30. Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank citation ranking: bringing order to the web. Technical report, Stanford Digital Library Technologies Project (1998)

    Google Scholar 

  31. Pavlovic, D.: Network as a computer: ranking paths to find flows. In: Hirsch, E.A., Razborov, A.A., Semenov, A., Slissenko, A. (eds.) CSR 2008. LNCS, vol. 5010, pp. 384–397. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-79709-8_38. arxiv.org:0802.1306

    Chapter  MATH  Google Scholar 

  32. Pavlovic, D., Meadows, C.: Deriving authentication for pervasive security. In: McLean, J. (ed.) Proceedings of the ISTPS 2008, 15 p. ACM (2008)

    Google Scholar 

  33. Pavlovic, D., Meadows, C.: Actor-network procedures. In: Ramanujam, R., Ramaswamy, S. (eds.) ICDCIT 2012. LNCS, vol. 7154, pp. 7–26. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28073-3_2. arxiv.org:1106.0706

    Chapter  Google Scholar 

  34. Pavlovic, D., Meadows, C.: Deriving ephemeral authentication using channel axioms. In: Christianson, B., Malcolm, J.A., Matyáš, V., Roe, M. (eds.) Security Protocols 2009. LNCS, vol. 7028, pp. 240–261. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-36213-2_27

    Chapter  Google Scholar 

  35. Pavlović, D., Escardó, M.: Calculus in coinductive form. In: Pratt, V. (ed.) Proceedings of Thirteenth Annual IEEE Symposium on Logic in Computer Science, pp. 408–417. IEEE Computer Society (1998)

    Google Scholar 

  36. Popper, K.R.: Conjectures and Refutations: The Growth of Scientific Knowledge. Classics Series. Routledge, Abingdon (2002)

    Google Scholar 

  37. Rogaway, P.: The moral character of cryptographic work. IACR Cryptology ePrint Archive 2015:1162 (2015)

    Google Scholar 

  38. Saari, D.G.: Basic Geometry of Voting. Basic Geometry of Voting Series. Springer, Heidelberg (1995). https://doi.org/10.1007/978-3-642-57748-2

    Book  MATH  Google Scholar 

  39. Schoeman, F.D.: Philosophical Dimensions of Privacy: An Anthology. Cambridge University Press, Cambridge (1984)

    Google Scholar 

  40. Shannon, C.E.: Communication theory of secrecy systems. Bell Syst. Tech. J. 28(4), 656–715 (1949)

    Article  MathSciNet  Google Scholar 

  41. Suzumura, K.: Rational Choice, Collective Decisions, and Social Welfare. Cambridge University Press, Cambridge (2009)

    Google Scholar 

  42. Sweeney, L.: Weaving technology and policy together to maintain confidentiality. J. Law Med. Ethics 25, 98–110 (1997)

    Article  Google Scholar 

  43. Sweeney, L.: Achieving k-anonymity privacy protection using generalization and suppression. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 10(5), 571–588 (2002)

    Article  MathSciNet  Google Scholar 

  44. Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 10(5), 557–570 (2002)

    Article  MathSciNet  Google Scholar 

  45. Warren, S.D., Brandeis, L.D.: The right to privacy. Harvard Law Rev. 4(5), 193–220 (1890)

    Article  Google Scholar 

  46. Wikipedia. Cambridge Analytica. wikipedia.org/wiki/Cambridge_Analytica

  47. Zuboff, S.: The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs, New York (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dusko Pavlovic .

Editor information

Editors and Affiliations

Additional information

Dedicated to Catherine Meadows

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Castiglione, J., Pavlovic, D., Seidel, PM. (2019). Privacy Protocols. In: Guttman, J., Landwehr, C., Meseguer, J., Pavlovic, D. (eds) Foundations of Security, Protocols, and Equational Reasoning. Lecture Notes in Computer Science(), vol 11565. Springer, Cham. https://doi.org/10.1007/978-3-030-19052-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-19052-1_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19051-4

  • Online ISBN: 978-3-030-19052-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics