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Statistical Disclosure Control

Statistical Disclosure Control. Presented by. Peter-Paul de Wolf, Statistics Netherlands (CBS). Content . Introduction What’s the problem? Specific for business statistics Formalising the problem What to do? Methods Software Summary. Introduction.

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Statistical Disclosure Control

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  1. StatisticalDisclosure Control

  2. Presented by • Peter-Paul de Wolf, • Statistics Netherlands (CBS)

  3. Content • Introduction • What’s the problem? • Specific for business statistics • Formalising the problem • What to do? • Methods • Software • Summary

  4. Introduction • General definition of confidential data: Data cannotbepublished “as is” • Bylaw (e.g. statisticallaw) • Sensitive data (what’ssensitive?) • Respondent considersitconfidential • …

  5. Introduction • Physicalprotection • Entrance • Network • Legal protection • Oath • Statistical Disclosure Control • Protection of statistical output

  6. What’s the problem? Statistical output • Microdata • Notoften in case of business data • Obvious: each record represents a single respondent • Tabular data • In business data often magnitude tables • Sometimesfrequencytables • But: aggregated data?!?!?!?

  7. What’s the problem (frequencytable) • Cellvalueitselfnotsensitive: • Allcontributions are equal (1) • Spanning variables • Indentifying, e.g. NACE, Region • Sensitive, e.g. “environmentaloffence” (illegal dumping of waste, illegalfishing, oilspills, …)

  8. What’s the problem (frequencytable) Example: number of ship-owners Environmental offence Region Yes No Total … A 9 0 9 ...

  9. What’s the problem (frequencytable) Example: number of ship-owners Environmental offence Region Yes No Total … B 14 2 16 ...

  10. What’s the problem (frequencytable) Example: number of ship-owners Environmental offence Region Yes No Total … C 1 1 2 ...

  11. What’s the problem (magnitude table) Turnover (106 €) of instrument producing companies Region A B C Total Harps 58 151 47 123 36 98 141 372 Organs 71 16 124 21 24 9 219 46 Pianos 92 5 157 2 59 1 308 8 Other 800 302 934 362 651287 2385 951 Total 1021474 1262 508 770395 3053 1377

  12. What’s the problem (magnitude table) Turnover (106 €) of instrument producing companies Region A B C Total Harps 58 151 47 123 36 98 141 372 Organs 71 16 124 21 24 9 219 46 Pianos 92 5 157 2 59 1 308 8 Other 800 302 934 362 651287 2385 951 Total 1021474 1262 508 770395 3053 1377 ?

  13. Formalising the problem Supposecell (Piano, A) consists of Company X: 81106€ Company Y: 5106€ Otherthree: 2106€each Total : 92106 € 92 – 5 = 87 is within 7.4%!

  14. Formalising the problem General, objectiverulesneeded • Thresholdrule • Dominancerule or (n,k)-rule • p%-rule p%-rule is favoured over (n,k)-ruleandimplies minimum of 3 contributors

  15. Whatto do? • Redesigntable • Combine rows/columns • Define different categories • Rounding • Addnoise • Cellsuppression

  16. Cellsuppression Region A B C D Total Harps 58 47 36 89 230 Organs 71124 24 31 250 Pianos 92 157 59 28 336 Other 800 934 651 742 3127 Total1021 1262 770 890 3943

  17. Cellsuppression Region A B C D Total Harps 58 47 36 89 230 Organs 71 124 24 31 250 Pianos 92 157 59 28 336 Other 800 934 651 742 3127 Total1021 1262 770 890 3943 X X X

  18. Cellsuppression Region A B C D Total Harps 58 47 36 89 230 Organs 71 124 24 31 250 Pianos 92 157 59 28 336 Other 800 934 651 742 3127 Total1021 1262 770 890 3943 X X X X X X

  19. Cellsuppression Region A B C D Total Harps 58 47 36 89 230 Organs 71 124 24 31 250 Pianos 92 157 59 28 336 Other 800 934 651 742 3127 Total1021 1262 770 890 3943 X X X X X X X X X

  20. Cellsuppression Region A B C D Total Harps 58 47 36 89 230 Organs 71 124 24 31 250 Pianos 92 157 59 28 336 Other 800 934 651 742 3127 Total1021 1262 770 890 3943 X X X X X X X X X

  21. Software Latestversioncanbe found on http://neon.vb.cbs.nl/casc New Open Source versionavailable end 2014

  22. Contact/info • Glossary, handbook, project info • http://neon.vb.cbs.nl/casc • Wileybook • pp.dewolf@cbs.nl

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