Computer Science – Databases
Scientific paper
2012-02-16
Computer Science
Databases
13 pages and 7 figures
Scientific paper
So far, privacy models follow two paradigms. The first paradigm, termed inferential privacy in this paper, focuses on the risk due to statistical inference of sensitive information about a target record from other records in the database. The second paradigm, known as differential privacy, focuses on the risk to an individual when included in, versus when not included in, the database. The contribution of this paper consists of two parts. The first part presents a critical analysis on differential privacy with two results: (i) the differential privacy mechanism does not provide inferential privacy, (ii) the impossibility result about achieving Dalenius's privacy goal [5] is based on an adversary simulated by a Turing machine, but a human adversary may behave differently; consequently, the practical implication of the impossibility result remains unclear. The second part of this work is devoted to a solution addressing three major drawbacks in previous approaches to inferential privacy: lack of flexibility for handling variable sensitivity, poor utility, and vulnerability to auxiliary information.
Fu Ada Waichee
Wang Ke
Wang Peng
Wong Raywong Chi-Wing
No associations
LandOfFree
Inferential or Differential: Privacy Laws Dictate does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Inferential or Differential: Privacy Laws Dictate, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Inferential or Differential: Privacy Laws Dictate will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-34955