On the security of noise addition for privacy in statistical databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3050, Issue , 2004, Pages 149-161

  Domingo Ferrer, Josep ^a   Sebé, Francesc ^a   Castellà Roca, Jordi ^a  

^a UNIVERSITAT ROVIRA I VIRGILI   (Spain)

Author keywords

Data security; Noise addition; Respondents' privacy; Statistical database protection; Statistical disclosure control; Statistical disclosure limitation

Indexed keywords

DATABASE SYSTEMS; SECURITY OF DATA; STATISTICS;

CRITICAL ANALYSIS; MICRODATA; NOISE ADDITION; PRIVACY IN STATISTICAL DATABASE; STATISTICAL DATABASE; STATISTICAL DISCLOSURE CONTROL; STATISTICAL DISCLOSURE LIMITATIONS;

DATA PRIVACY;

EID: 35048834229     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-25955-8_12     Document Type: Article

References (18)

1. R. Agrawal and R. Srikant, "Privacy preserving data mining", in Proceedings of the ACM SIGMOD, pp. 439-450, 2000.
2. D. Agrawal and C. C. Aggarwal, "On the design and quantification of privacy preserving data mining algorithms", in Proceedings of the 20th Symposium on Principles of Database Systems, Santa Barbara, California, USA, May 2001.
3. R. Brand, "Microdata protection through noise addition", Lecture Notes in Computer Science, vol. 2316, pp. 97-116, 2002.
4. Volume title Inference Control in Statistical Databases, ed. J. Domingo-Ferrer. Berlin: Springer-Verlag, 2002.
5. R. Brand, "Tests of the applicability of Sullivan's algorithm to synthetic data and real business data in official statistics", Deliverable 1.1-D1, project IST-2000-25069 CASC, 28 August 2002. http://neon.vb.cbs.nl/casc
6. J. Domingo-Ferrer and V. Torra, "Disclosure protection methods and information loss for microdata", in Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, eds. P. Doyle, J. Lane, J. Theeuwes and L. Zayatz. Amsterdam: North-Holland, 2001, pp. 91-110.
7. European Commission, "Open consultation on "Trust Barriers for B2B e-Marketplaces". Presentation of the main results". Brussels: EC, June 2002. Available from http://www.privacyexchange.org/iss/surveys
8. Jupiter Media Metrix, "Seventy percent of US consumers worry about online privacy, but few take protective action" (survey summary). New York: JMM, June 3, 2002. Available from http://www.jupiterresearch.com/xp/jmm/press/ 2002/pr_060302.html
9. H. Kargupta, S. Datta, Q. Wang and K. Sivakumar, "On the privacy preserving properties of random data perturbation techniques", in 3rd IEEE International Conference on Data Mining, Nov. 2003, pp. 99-106. Winner of the Best Paper Award.
10. Extended version entitled "Random data perturbation techniques and privacy preserving data mining".
11. J. J. Kim, "A method for limiting disclosure in microdata based on random noise and transformation", in Proceedings of the Section on Survey Research Methods. American Statistical Association, 1986, pp. 303-308.
12. J. J. Kim, "Subpopulation estimation for the masked data", in Proceedings of the Section on Survey Research Methods. American Statistical Association, 1990, pp. 456-461.
13. Princeton Survey Research Associates, "A matter of trust: What users want from Web sites". Yonkers, NY: Consumer WebWatch, April 16, 2002. Available from http://www.consumerwebwatch.org/news/1-abstract.htm
14. G. M. Roque, Masking Microdata Files with Mixtures of Multivariate Normal Distributions, unpublished Ph. D. Thesis, University of California at Riverside, 2000.
15. G. R. Sullivan, The Use of Added Error to Avoid Disclosure in Microdata Releases, unpublished Ph. D. Thesis, Iowa State University, 1989.
16. P. Tendick, "Optimal noise addition for preserving confidentiality in multivariate data", Journal of Statistical Planning and Inference, vol. 27, pp. 341-353, 1991.
17. P. Tendick and N. Matloff, "A modified random perturbation method for database security", ACM Transactions on Database Systems, vol. 19, pp. 47-63.
18. L. Willenborg and T. de Waal, Elements of Statistical Disclosure Control. New York: Springer-Verlag, 2001.