Skip to main content

Analyzing Randomized Response Mechanisms Under Differential Privacy

  • Conference paper
  • First Online:
Information Security (ISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9866))

Included in the following conference series:

Abstract

The randomized response technique was first introduced by Warner in 1965 [27] as a technique to survey sensitive questions. Since it is considered to protect the respondent’s privacy, many variants and applications have been proposed in the literature. Unfortunately, the randomized response and its variants have not been well evaluated from the privacy viewpoint historically. In this paper, we evaluate them by using differential privacy. Specifically, we show that some variants have a tradeoff between the privacy and utility, and that the “negative” survey technique obtains negative results.

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

References

  1. Abul-Ela, A.L.A., Greenberg, G.G., Horvitz, D.G.: A multi-proportions randomized response model. J. Am. Stat. Assoc. 62(319), 990–1008 (1967)

    Article  MathSciNet  Google Scholar 

  2. Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer and Communications Security, pp. 901–914. ACM (2013)

    Google Scholar 

  3. Aoki, S., Iwai, M., Sezaki, K.: Limited negative surveys: privacy-preserving participatory sensing. In: 2012 IEEE 1st International Conference on Cloud Networking (CLOUDNET), pp. 158–160. IEEE (2012)

    Google Scholar 

  4. Aoki, S., Sezaki, K.: Negative surveys with randomized response techniques for privacy-aware participatory sensing. IEICE Trans. Commun. 97(4), 721–729 (2014)

    Article  Google Scholar 

  5. Dankar, F.K., El Emam, K.: The application of differential privacy to health data. In: Proceedings of the 2012 Joint EDBT/ICDT Workshops, pp. 158–166. ACM (2012)

    Google Scholar 

  6. Dietz, P., Striegel, H., Franke, A.G., Lieb, K., Simon, P., Ulrich, R.: Randomized response estimates for the 12-month prevalence of cognitive-enhancing drug use in university students. Pharmacother. J. Hum. Pharmacol. Drug Ther. 33(1), 44–50 (2013)

    Article  Google Scholar 

  7. Du, W., Zhan, Z.: Using randomized response techniques for privacy-preserving data mining. In: Proceedings of the ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 505–510. ACM (2003)

    Google Scholar 

  8. Dwork, C.: Differential privacy. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1–12. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  9. Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci. 9(3–4), 211–407 (2014)

    MathSciNet  MATH  Google Scholar 

  10. Eichhorn, B.H., Hayre, L.S.: Scrambled randomized response methods for obtaining sensitive quantitative data. J. Stat. Plan. Infer. 7(4), 307–316 (1983)

    Article  Google Scholar 

  11. Erlingsson, Ú., Pihur, V., Korolova, A.: RAPPOR: randomized aggregatable privacy-preserving ordinal response. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1054–1067. ACM (2014)

    Google Scholar 

  12. Esponda, F.: Negative surveys. arXiv preprint math/0608176 (2006)

    Google Scholar 

  13. Fidler, D.S., Kleinknecht, R.E.: Randomized response versus direct questioning: two data-collection methods for sensitive information. Psychol. Bull. 84(5), 1045 (1977)

    Article  Google Scholar 

  14. Friedman, A., Schuster, A.: Data mining with differential privacy. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 493–502. ACM (2010)

    Google Scholar 

  15. Greenberg, B.G., Abul-Ela, A.L.A., Simmons, W.R., Horvitz, D.G.: The unrelated question randomized response model: theoretical framework. J. Am. Stat. Assoc. 64(326), 520–539 (1969)

    Article  MathSciNet  Google Scholar 

  16. Groat, M.M., Edwards, B., Horey, J., He, W., Forrest, S.: Enhancing privacy in participatory sensing applications with multidimensional data. In: 2012 IEEE International Conference on Pervasive Computing and Communications (PerCom), pp. 144–152. IEEE (2012)

    Google Scholar 

  17. Horey, J., Forrest, S., Groat, M.: Reconstructing spatial distributions from anonymized locations. In: 2012 IEEE 28th International Conference on Data Engineering Workshops (ICDEW), pp. 243–250. IEEE (2012)

    Google Scholar 

  18. Horey, J., Groat, M.M., Forrest, S., Esponda, F.: Anonymous data collection in sensor networks. In: Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, MobiQuitous 2007, pp. 1–8. IEEE (2007)

    Google Scholar 

  19. Huang, Z., Du, W.: OptRR: optimizing randomized response schemes for privacy-preserving data mining. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 705–714. IEEE (2008)

    Google Scholar 

  20. Inan, A., Kantarcioglu, M., Ghinita, G., Bertino, E.: Private record matching using differential privacy. In: Proceedings of the 13th International Conference on Extending Database Technology, pp. 123–134. ACM (2010)

    Google Scholar 

  21. Kuk, A.Y.: Asking sensitive questions indirectly. Biometrika 77(2), 436–438 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  22. Lara, D., García, S.G., Ellertson, C., Camlin, C., Suárez, J.: The measure of induced abortion levels in Mexico using random response technique. Sociol. Meth. Res. 35(2), 279–301 (2006)

    Article  MathSciNet  Google Scholar 

  23. Mangat, N.S.: An improved randomized response strategy. J. R. Stat. Soc. Ser. B (Methodol.) 56(1), 93–95 (1994)

    MathSciNet  MATH  Google Scholar 

  24. Mangat, N., Singh, R.: An alternative randomized response procedure. Biometrika 77(2), 439–442 (1990)

    Article  MathSciNet  MATH  Google Scholar 

  25. Polat, H., Du, W.: Achieving private recommendations using randomized response techniques. In: Ng, W.-K., Kitsuregawa, M., Li, J., Chang, K. (eds.) PAKDD 2006. LNCS (LNAI), vol. 3918, pp. 637–646. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  26. Quercia, D., Leontiadis, I., McNamara, L., Mascolo, C., Crowcroft, J.: SpotME if you can: randomized responses for location obfuscation on mobile phones. In: 2011 31st International Conference on Distributed Computing Systems (ICDCS), pp. 363–372. IEEE (2011)

    Google Scholar 

  27. Warner, S.L.: Randomized response: a survey technique for eliminating evasive answer bias. J. Am. Stat. Assoc. 60(309), 63–69 (1965)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Atsushi Waseda .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Waseda, A., Nojima, R. (2016). Analyzing Randomized Response Mechanisms Under Differential Privacy. In: Bishop, M., Nascimento, A. (eds) Information Security. ISC 2016. Lecture Notes in Computer Science(), vol 9866. Springer, Cham. https://doi.org/10.1007/978-3-319-45871-7_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-45871-7_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45870-0

  • Online ISBN: 978-3-319-45871-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics