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Privacy Preserving Data Dissemination

Privacy Preserving Data Dissemination. Dr. Murat Kantarcioglu (muratk@utdallas.edu) Harichandan Roy ( harichandan.roy@utdallas.edu) Data Security and Privacy Lab UT Dallas. What is Task 1?. Given- case/control datasets Desired result- perturbed datasets. Method applied. snps. snps.

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Privacy Preserving Data Dissemination

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  1. Privacy Preserving Data Dissemination Dr. Murat Kantarcioglu (muratk@utdallas.edu) HarichandanRoy (harichandan.roy@utdallas.edu) Data Security and Privacy Lab UT Dallas

  2. What is Task 1? • Given- case/control datasets • Desired result- perturbed datasets Method applied snps snps Case Control Perturbed snps Desired Result anonymous

  3. Proposed Method: NCBI Added Noise • Main Idea: Keep the significant SNPs MAFs, add noise to non-significant SNPs MAFs • For significant snips • Define significant and non-significant snips based on p-value using pLink (significant if p is less than 0.05) • Keep MAF as it is in case

  4. Proposed Method: NCBI Added Noise • For non-significant snips • Take variance of MAF in case • Get gaussian random values, noises, with mean = 0 and std = (a*Math.sqrt(var)), where a = 3. • Finally, add noise to NCBI MAF • If NCBI MAF does not exist, add noise to average MAF of case and control • Order all perturbed MAFs as in case file

  5. Flow Diagram

  6. Results • For chr2, • Used NCBI Added Noise Method • Got power ≈ 8 <20 • For chr10, • Used Average Case/Control Method • Got power ≈ 8 <20 • Power ≈ 8 <20 • It means desired level of privacy is preserved • Results are not always same

  7. Other Tries

  8. Questions?

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