Application of a Statistical Disclosure Control Techniques Based on Multiplicative Noise

Title & Authors
Application of a Statistical Disclosure Control Techniques Based on Multiplicative Noise
Kim, Young-Won; Kim, Tae-Yeon; Ki, Kye-Nam;

Abstract
Multiplicative noise model is the one of popular method for masking continuous variables. In this paper, we propose the transformation on the variable to which random noise was multiplied. An advantage of the masking method using proposed transformation is that the masking data users can obtain the unbiased values of mean and variance of original (unmasked) data. We also consider the data utility and correlation structure of variables when we apply the proposed multiplicative noise scheme. To investigate the properties of the method of masking based on multiplicative noise, a simulation study has been conducted using the 2008 Householder Income and Expenditure Survey data.
Keywords
Data utility;disclosure risk;multiplicative noise model;statistical disclosure control;
Language
Korean
Cited by
1.
Study on a Measurement of Disclosure Risk of Microdata by Similarity,;;;

응용통계연구, 2012. vol.25. 5, pp.743-755
2.
마이크로데이터 공표를 위한 통계적 노출제어 방법론 고찰,박민정;김항준;

응용통계연구, 2016. vol.29. 6, pp.1041-1059
3.
확률화응답기법을 이용한 연속형 변수의 마스킹 방법,김현지;손창균;

Journal of the Korean Data Analysis Society, 2015. vol.17. 4B, pp.1957-1967
1.
Study on a Measurement of Disclosure Risk of Microdata by Similarity, Korean Journal of Applied Statistics, 2012, 25, 5, 743
2.
Estimating nonlinear regression with and without change-points by the LAD method, Annals of the Institute of Statistical Mathematics, 2011, 63, 4, 717
3.
Penalized least absolute deviations estimation for nonlinear model with change-points, Statistical Papers, 2011, 52, 2, 371
4.
Empirical likelihood for nonlinear models with missing responses, Journal of Statistical Computation and Simulation, 2013, 83, 4, 739
5.
Statistical disclosure control for public microdata: present and future, Korean Journal of Applied Statistics, 2016, 29, 6, 1041
6.
Least absolute value regression: recent contributions, Journal of Statistical Computation and Simulation, 2005, 75, 4, 263
References
1.
김규성 (2009). 마이크로데이터 제공과 통계적 노출조절기법, <한국통계학회논문집>, 16, 1-11.

2.
정동명, 김종익, 강동환 (2007). 인구센서스자료의 비밀보호방법, <응용통계연구>, 12, 95-120.

3.
정동명, 김종익, 김경미 (2009). 잡음을 이용한 가계조사자료의 정보노출제한방법, <응용통계연구>, 22, 141-151.

4.
정동명, 정미옥 (2008). 인구주택총조사 마이크로자료의 개인정보 노출제한방법, <응용통계연구>, 21, 313-325.

5.
통계청 (2008). 가계조사 조사지침서.

6.
Dalenius, T. and Reiss, S. P. (1982). Data swapping: A technique for disclosure control, Journal of Statistical Planning and Inference, 6, 73-85.

7.
Fuller, W. A. (1993). Masking procedures for microdata disclosure limitation, Journal of Official Statisitcs, 9, 383-406.

8.
Karr, A. F., Kohnen, C. N., Oganian, A., Reiter, J. P. and Sanil, A. P. (2006). A framework for evaluating the utility of data altered to protect confidentiality, The American Statistician, 60, 1-9.

9.
Kim, J. (1986). A method for limiting disclosure in microdata based on random noise and transformation, American Statistical Association Proceedings of the Section on Survey Research Methods, 303-308.

10.
Kim, J. (2007). Application of the truncated triangular and trapezoidal distributions for developing multi-plicative noise, American Statistical Association Proceedings of the Section on Survey Research Methods, 2723-2729.

11.
Kim, J. and Winkler, W. E. (2001). Multiplicative noise for masking continuous data, American Statistical Association Proceedings of the Section on Survey Research Methods, CD-ROM.

12.
Torra, V. (2004). Microaggregation for categorical variavbles: A median based approach, In Domingo-Ferrer, J. and Torra, V. Editors, Privacy in Statistical Databases, Lecture Notes in Computer Science, 3050, 162-174.

13.
Woo, M. J., Reiter, P., Anna, O. and Karr, A. F. (2009). Global measures of data utility for microdata masked for dislosure limitation, The Journal of Privacy and Confidentiality, 1, 111-124.