A Method for Preservation of Privacy in Data Mining Processes

被引:0
|
作者
Liang, Danyan [1 ]
Busch, Peter [2 ]
Picoto, Winnie [3 ]
机构
[1] Shanghai Ouji Imp & Exp Co Ltd, Shanghai, Peoples R China
[2] Macquarie Univ, Dept Comp, N Ryde, NSW 2109, Australia
[3] Univ Lisbon, ISEG, P-1200781 Lisbon, Portugal
关键词
Data Mining; Business Process Modelling; Privacy; Visio; BIG DATA; ANALYTICS;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
Most ethical issues in data mining have paid more attention to government excesses, while ignoring the critical issue of national security and how data mining can be used to improve it. This paper illustrates how technology can be used to ensure personal privacy is preserved while security agencies use data mining tools to identify behavior patterns of individuals, which may form a security threat to the country. We show that Anonymized data (ANNA) software can be integrated with Non-Obvious Relationship Awareness (NORA) to encrypt data before mining. Understanding the types of users in the process of data mining can help determine privacy concerns of every user and thus develop appropriate measures to ensure privacy is preserved. We also demonstrate how process models can be designed for standardizing the data mining process to track individuals or organizations with access to metadata, retrieve personal profiles and also keep such profiles private.
引用
收藏
页码:203 / 223
页数:21
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