IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v17y2006i3p254-270.html
   My bibliography  Save this article

Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data

Author

Listed:
  • Xiao-Bai Li

    (College of Management, University of Massachusetts Lowell, Lowell, Massachusetts 01854)

  • Sumit Sarkar

    (School of Management, University of Texas at Dallas, Richardson, Texas 75080)

Abstract

To respond to growing concerns about privacy of personal information, organizations that use their customers' records in data-mining activities are forced to take actions to protect the privacy of the individuals involved. A common practice for many organizations today is to remove identity-related attributes from the customer records before releasing them to data miners or analysts. We investigate the effect of this practice and demonstrate that many records in a data set could be uniquely identified even after identity-related attributes are removed. We propose a perturbation method for categorical data that can be used by organizations to prevent or limit disclosure of confidential data for identifiable records when the data are provided to analysts for classification, a common data-mining task. The proposed method attempts to preserve the statistical properties of the data based on privacy protection parameters specified by the organization. We show that the problem can be solved in two phases, with a linear programming formulation in Phase I (to preserve the first-order marginal distribution), followed by a simple Bayes-based swapping procedure in Phase II (to preserve the joint distribution). Experiments conducted on several real-world data sets demonstrate the effectiveness of the proposed method.

Suggested Citation

  • Xiao-Bai Li & Sumit Sarkar, 2006. "Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data," Information Systems Research, INFORMS, vol. 17(3), pages 254-270, September.
    • Handle: RePEc:inm:orisre:v:17:y:2006:i:3:p:254-270
    DOI: 10.1287/isre.1060.0095
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.1060.0095
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.1060.0095?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sumit Dutta Chowdhury & George T. Duncan & Ramayya Krishnan & Stephen F. Roehrig & Sumitra Mukherjee, 1999. "Disclosure Detection in Multivariate Categorical Databases: Auditing Confidentiality Protection Through Two New Matrix Operators," Management Science, INFORMS, vol. 45(12), pages 1710-1723, December.
    2. Rathindra Sarathy & Krishnamurty Muralidhar, 2002. "The Security of Confidential Numerical Data in Databases," Information Systems Research, INFORMS, vol. 13(4), pages 389-403, December.
    3. Robert Garfinkel & Ram Gopal & Paulo Goes, 2002. "Privacy Protection of Binary Confidential Data Against Deterministic, Stochastic, and Insider Threat," Management Science, INFORMS, vol. 48(6), pages 749-764, June.
    4. Krishnamurty Muralidhar & Rahul Parsa & Rathindra Sarathy, 1999. "A General Additive Data Perturbation Method for Database Security," Management Science, INFORMS, vol. 45(10), pages 1399-1415, October.
    5. Duncan, George & Lambert, Diane, 1989. "The Risk of Disclosure for Microdata," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(2), pages 207-217, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Robert Garfinkel & Ram Gopal & Steven Thompson, 2007. "Releasing Individually Identifiable Microdata with Privacy Protection Against Stochastic Threat: An Application to Health Information," Information Systems Research, INFORMS, vol. 18(1), pages 23-41, March.
    2. Xiao-Bai Li & Sumit Sarkar, 2009. "Against Classification Attacks: A Decision Tree Pruning Approach to Privacy Protection in Data Mining," Operations Research, INFORMS, vol. 57(6), pages 1496-1509, December.
    3. Shaobo Li & Matthew J. Schneider & Yan Yu & Sachin Gupta, 2023. "Reidentification Risk in Panel Data: Protecting for k -Anonymity," Information Systems Research, INFORMS, vol. 34(3), pages 1066-1088, September.
    4. Matthew J. Schneider & Shawn Mankad, 2021. "A Two-Stage Authorship Attribution Method Using Text and Structured Data for De-Anonymizing User-Generated Content," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(3), pages 66-83, September.
    5. Xiao-Bai Li & Sumit Sarkar, 2011. "Protecting Privacy Against Record Linkage Disclosure: A Bounded Swapping Approach for Numeric Data," Information Systems Research, INFORMS, vol. 22(4), pages 774-789, December.
    6. Weiyin Hong & Frank K. Y. Chan & James Y. L. Thong, 2021. "Drivers and Inhibitors of Internet Privacy Concern: A Multidimensional Development Theory Perspective," Journal of Business Ethics, Springer, vol. 168(3), pages 539-564, January.
    7. Xiao-Bai Li & Sumit Sarkar, 2013. "Class-Restricted Clustering and Microperturbation for Data Privacy," Management Science, INFORMS, vol. 59(4), pages 796-812, April.
    8. Zike Cao & Kai-Lung Hui & Hong Xu, 2018. "An Economic Analysis of Peer Disclosure in Online Social Communities," Information Systems Research, INFORMS, vol. 29(3), pages 546-566, September.
    9. Nigel Melville & Michael McQuaid, 2012. "Research Note ---Generating Shareable Statistical Databases for Business Value: Multiple Imputation with Multimodal Perturbation," Information Systems Research, INFORMS, vol. 23(2), pages 559-574, June.
    10. Haibing Lu & Jaideep Vaidya & Vijayalakshmi Atluri & Yingjiu Li, 2015. "Statistical Database Auditing Without Query Denial Threat," INFORMS Journal on Computing, INFORMS, vol. 27(1), pages 20-34, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joseph B. Kadane & Ramayya Krishnan & Galit Shmueli, 2006. "A Data Disclosure Policy for Count Data Based on the COM-Poisson Distribution," Management Science, INFORMS, vol. 52(10), pages 1610-1617, October.
    2. Syam Menon & Sumit Sarkar & Shibnath Mukherjee, 2005. "Maximizing Accuracy of Shared Databases when Concealing Sensitive Patterns," Information Systems Research, INFORMS, vol. 16(3), pages 256-270, September.
    3. Syam Menon & Sumit Sarkar, 2007. "Minimizing Information Loss and Preserving Privacy," Management Science, INFORMS, vol. 53(1), pages 101-116, January.
    4. Haibing Lu & Jaideep Vaidya & Vijayalakshmi Atluri & Yingjiu Li, 2015. "Statistical Database Auditing Without Query Denial Threat," INFORMS Journal on Computing, INFORMS, vol. 27(1), pages 20-34, February.
    5. Xiao-Bai Li & Sumit Sarkar, 2013. "Class-Restricted Clustering and Microperturbation for Data Privacy," Management Science, INFORMS, vol. 59(4), pages 796-812, April.
    6. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    7. Rathindra Sarathy & Krishnamurty Muralidhar, 2002. "The Security of Confidential Numerical Data in Databases," Information Systems Research, INFORMS, vol. 13(4), pages 389-403, December.
    8. Amalia R. Miller & Catherine Tucker, 2009. "Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records," Management Science, INFORMS, vol. 55(7), pages 1077-1093, July.
    9. Robert Garfinkel & Ram Gopal & Steven Thompson, 2007. "Releasing Individually Identifiable Microdata with Privacy Protection Against Stochastic Threat: An Application to Health Information," Information Systems Research, INFORMS, vol. 18(1), pages 23-41, March.
    10. S F Roehrig & R Padman & R Krishnan & G T Duncan, 2011. "Exact and heuristic methods for cell suppression in multi-dimensional linked tables," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 291-304, February.
    11. Xiao-Bai Li & Sumit Sarkar, 2009. "Against Classification Attacks: A Decision Tree Pruning Approach to Privacy Protection in Data Mining," Operations Research, INFORMS, vol. 57(6), pages 1496-1509, December.
    12. Xiao-Bai Li & Jialun Qin, 2017. "Anonymizing and Sharing Medical Text Records," Information Systems Research, INFORMS, vol. 28(2), pages 332-352, June.
    13. Trottini, Mario & Muralidhar, Krish & Sarathy, Rathindra, 2011. "Maintaining tail dependence in data shuffling using t copula," Statistics & Probability Letters, Elsevier, vol. 81(3), pages 420-428, March.
    14. Shlomo, Natalie & Skinner, Chris J., 2010. "Assessing the protection provided by misclassification-based disclosure limitation methods for survey microdata," LSE Research Online Documents on Economics 39119, London School of Economics and Political Science, LSE Library.
    15. Skinner, Chris J. & Shlomo, Natalie, 2008. "Assessing identification risk in survey microdata using log-linear models," LSE Research Online Documents on Economics 39112, London School of Economics and Political Science, LSE Library.
    16. Natalie Shlomo & Chris Skinner, 2022. "Measuring risk of re‐identification in microdata: State‐of‐the art and new directions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1644-1662, October.
    17. Amanda M. Y. Chu & Benson S. Y. Lam & Agnes Tiwari & Mike K. P. So, 2019. "An Empirical Study of Applying Statistical Disclosure Control Methods to Public Health Research," IJERPH, MDPI, vol. 16(22), pages 1-17, November.
    18. Sumit Dutta Chowdhury & George T. Duncan & Ramayya Krishnan & Stephen F. Roehrig & Sumitra Mukherjee, 1999. "Disclosure Detection in Multivariate Categorical Databases: Auditing Confidentiality Protection Through Two New Matrix Operators," Management Science, INFORMS, vol. 45(12), pages 1710-1723, December.
    19. Braathen, Christian & Thorsen, Inge & Ubøe, Jan, 2022. "Adjusting for Cell Suppression in Commuting Trip Data," Discussion Papers 2022/13, Norwegian School of Economics, Department of Business and Management Science.
    20. Rathindra Sarathy & Krishnamurty Muralidhar & Rahul Parsa, 2002. "Perturbing Nonnormal Confidential Attributes: The Copula Approach," Management Science, INFORMS, vol. 48(12), pages 1613-1627, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:17:y:2006:i:3:p:254-270. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.