Digital Library[ Search Result ]

Search : [ author: 백인철 ] (2)

A Differential-Privacy Technique for Publishing Density-based Clustering Results

Namil Kim, Incheol Baek, Hyubjin Lee, Minsoo Kim, Yon Dohn Chung

http://doi.org/10.5626/JOK.2024.51.4.380

Clustering techniques group data with similar characteristics. Density-Based Spatial Clustering Analysis (DBSCAN) is widely used in various fields as it can detect outliers and is not affected by data distribution. However, the conventional DBSCAN method has a vulnerability where privacy-sensitive personal information in the original data can be easily exposed in the clustering results. Therefore, disclosing and distributing such data without appropriate privacy protection poses risks. This paper proposes a method to generate DBSCAN results that satisfy differential privacy. Additionally, a post-processing technique is introduced to effectively reduce noise introduced during the application of differential privacy and to process the data for future analysis. Through experiments, we observed that the proposed method enhances the utility of the data while satisfying differential privacy.

A Privacy-preserving Histogram Construction Method Guaranteeing the Differential Privacy

In Cheol Baek, Jongseon Kim, Yon Dohn Chung

http://doi.org/10.5626/JOK.2022.49.6.488

With the widespread use of data collection and analysis, the need for preserving the privacy of individuals is emerging. Various privacy models have been proposed to guarantee privacy while collecting and analyzing data in a privacy-preserving manner. Among various privacy models, the differential privacy stands as the de facto standard. In this paper, we propose a privacy-preserving histogram construction method guaranteeing differential privacy. The proposed method consists of histogram bin setting and frequency calculation stages. In the first stage, we use the Laplace mechanism to heuristic bin setting algorithms to select a differentially private number of bins. In the second stage, we use the Laplace mechanism to each frequency falling into the bins to output differentially private frequencies. We prove the proposed method guarantees differential privacy and compare the accuracy according to privacy budget values and distribution rates through experiments.


Search




Journal of KIISE

  • ISSN : 2383-630X(Print)
  • ISSN : 2383-6296(Electronic)
  • KCI Accredited Journal

Editorial Office

  • Tel. +82-2-588-9240
  • Fax. +82-2-521-1352
  • E-mail. chwoo@kiise.or.kr