Differentially Private Data Release through Multidimensional Partitioning

Autor:	Chun Yuan, Yonghui Xiao, Li Xiong
Rok vydání:	2010
Předmět:	Set (abstract data type) Data cube Theoretical computer science Computer science Interface (Java) Differential privacy Data mining Baseline (configuration management) computer.software_genre computer
Zdroj:	Lecture Notes in Computer Science ISBN: 9783642155451 Secure Data Management
Popis:	Differential privacy is a strong notion for protecting individual privacy in privacy preserving data analysis or publishing. In this paper, we study the problem of differentially private histogram release based on an interactive differential privacy interface. We propose two multidimensional partitioning strategies including a baseline cell-based partitioning and an innovative kd-tree based partitioning. In addition to providing formal proofs for differential privacy and usefulness guarantees for linear distributive queries, we also present a set of experimental results and demonstrate the feasibility and performance of our method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::bcdbc54c6387a4e44f83f1b9620d8c14 https://doi.org/10.1007/978-3-642-15546-8_11 Zobrazit plný text záznamu