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SUMMARY:The Challenge of Privacy Protection for Statistical Agencies - Joh
 n Abowd (U.S. Census Bureau\; Cornell University)
DTSTART:20160706T133000Z
DTEND:20160706T143000Z
UID:TALK66670@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Since the field of statistical disclosure limitation (SDL) was
  first formalized by Ivan Fellegi in 1972\, official statistical agencies 
 have recognized that their publications posed confidentiality risks for th
 e households and businesses who responded. For even longer\, agencies have
  protected the source data for those publications by using secure storage 
 methods and access authorization systems. In SDL\, Dalenius (1977) and\, i
 n computer science\, Goldwasser and Micali (1982) formalized what has beco
 me the modern approach to privacy protection in data publication: inferent
 ial disclosure limitation/semantic security. The modern approach to physic
 al data security centers on firewall and encryption technologies. And the 
 two sets of risks (disclosure through publication and disclosure through u
 nauthorized access) have become increasingly inter-related. It is importan
 t to recognize the distinct issues\, however. Secure multiparty computing 
 and the stronger fully homomorphic encryption are formal solutions to the 
 problem of permitting statistical computations without granting access to 
 the decrypted data. Privacy-protected query publication is a formal soluti
 on to the problem of insuring that inferential disclosures are bounded and
  that the bound is respected in all published tables. There are now tracta
 ble systems that combine secure multi-party computing with formal privacy 
 protection of the computed statistics (e.g.\, Shokri and Shmatikov 2015). 
 The challenge to statistical agencies is to learn how these systems work\,
  and move their own protection technologies in this direction. Private com
 panies like Google and Microsoft already do this. Statistical agencies mus
 t be prepared to explain the differences in their publication requirements
  and security protocols that distinguish their chosen data storage methods
  and publications from those used by private companies.<br><br>Related Lin
 ks<ul><li><a target="_blank" rel="nofollow">http://www.brookings.edu/~/med
 ia/Projects/BPEA/Spring-2015/2015a_abowd.pdf?la=en</a>&nbsp\;- Abowd-Schmu
 tte BPEA Spring 2015</li></ul>
LOCATION:Seminar Room 1\, Newton Institute
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