Deriving Private Information from Perturbed Data using IQR Based Approach

• Main Authors: GUO, Songtao, WU, Xintao, LI, Yingjiu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2006
• Subjects: Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/321; http://dx.doi.org/10.1109/ICDEW.2006.47
• Institution: Singapore Management University

Several randomized techniques have been proposed for privacy preserving data mining of continuous data. These approaches generally attempt to hide the sensitive data by randomly modifying the data values using some additive noise and aim to reconstruct the original distribution closely at an aggrega...