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Data Shuffling for Enhanced Confidential Data Protection: A Software Demonstration

This demonstration showcases a novel data shuffling method that integrates the advantages of data perturbation and swapping, designed to protect confidential data without introducing added noise. The technique preserves the original marginal distributions and monotonic relationships among variables, ensuring maximum protection against identity and value disclosure. It operates on a non-parametric basis, utilizing confidential and non-confidential variables effectively. The software is available in early beta versions for Java and Windows, and the software's capabilities and practical applications will be demonstrated in this session.

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Data Shuffling for Enhanced Confidential Data Protection: A Software Demonstration

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  1. Data Shuffling for Protecting Confidential Data A Software Demonstration • RathindraSarathy* and KrishMuralidhar** • * Oklahoma State University, Stillwater, OK 74078 USA (rathin.sarathy@okstate.edu) • ** University of Kentucky, Lexington, KY 40506, USA • (krishm@uky.edu)

  2. Data Shuffling • Method that: • Combines the strengths of data perturbation and data swapping • Shuffled data uses only original confidential values – no added noise or “unreasonable” values • Preserves marginals exactly and all monotonic relationships among variables (preserves pairwise rank order correlation closely) • Non-parametric method • Maximum protection against identity and value disclosure

  3. Technical Basis • X represents M confidential variables • S represents L non-confidential variables. • X is assumed numerical; S can be categorical or numerical variables. • Y represents the masked values of X. • Let R is rank order correlation matrix of {X, S}. Define variables as follows: X* and S* as:

  4. Technical Basis - continued

  5. Example Dataset – Shuffled data

  6. Example Dataset – Rank Order Correlations

  7. Example Dataset - Relationships

  8. Software Demo • Two versions are available – both in early Beta (Java and Windows) • Example shown earlier was run on Java version of software • We will demonstrate the software later

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