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Data Privacy

Data Privacy. October 30, 2007. k -anonymity. “A release provides k-anonymity protection if the information for each person contained in the release cannot be distinguished from at least k-1 individuals whose information also appears in the release.”

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Data Privacy

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  1. Data Privacy October 30, 2007

  2. k-anonymity • “A release provides k-anonymity protection if the information for each person contained in the release cannot be distinguished from at least k-1 individuals whose information also appears in the release.” http://privacy.cs.cmu.edu/people/sweeney/kanonymity.html

  3. De-identification and re-identification • Simplistic de-identification: remove obvious identifiers • Better de-identification: also k-anonymize and/or use statistical confidentiality techniques • Re-identification can occur through linking entries within the same database or to entries in external databases

  4. Examples • When RFID tags are sewn into every garment, how might we use this to identify and track people? • What if the tags are partially killed so only the product information is broadcast, not a unique ID? • How can a cellular provider identify an anonymous pre-paid cell phone user? • Other examples?

  5. Techniques for protecting privacy • Best • No collection of contact information • No collection of long term person characteristics • k-anonymity with large value of k • Good • No unique identifiers across databases • No common attributes across databases • Random identifiers • Contact information stored separately from profile or transaction information • Collection of long term personal characteristics on a low level of granularity • Technically enforced deletion of profile details at regular intervals

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