Utility Independent Privacy Preserving Data Mining - Horizontally Partitioned Data
نویسندگان
چکیده
منابع مشابه
Utility Independent Privacy Preserving Data Mining - Horizontally Partitioned Data
Micro data is a valuable source of information for research. However, publishing data about individuals for research purposes, without revealing sensitive information, is an important problem. The main objective of privacy preserving data mining algorithms is to obtain accurate results/rules by analyzing the maximum possible amount of data without unintended information disclosure. Data sets fo...
متن کاملPrivacy - Preserving Distributed Data Mining and Processing on Horizontally Partitioned Data
Kantarcıoğlu, Murat. Ph.D., Purdue University, August, 2005. Privacy-Preserving Distributed Data Mining and Processing on Horizontally Partitioned Data. Major Professor: Christopher W. Clifton. Data mining can extract important knowledge from large data collections, but sometimes these collections are split among various parties. Data warehousing, bringing data from multiple sources under a sin...
متن کاملPhoenix: Privacy Preserving Biclustering on Horizontally Partitioned Data
Emerging business models require organizations to collaborate with each other. This collaboration is usually in the form of distributed clustering to find optimal customer targets for effective marketing. This process is hampered by two problems (1) Inability of traditional clustering algorithm in finding local (subspace) patterns in distributed data and (2) Privacy policies of individual organ...
متن کاملPrivacy-Preserving Decision Tree Classification Over Horizontally Partitioned Data
Protection of privacy is one of important problems in data mining. The unwillingness to share their data frequently results in failure of collaborative data mining. This paper studies how to build a decision tree classifier under the following scenario: a database is horizontally partitioned into multiple pieces, with each piece owned by a particular party. All the parties want to build a decis...
متن کاملA Survey of Privacy-Preserving Methods Across Horizontally Partitioned Data
Data mining can extract important knowledge from large data collections, but sometimes these collections are split among various parties. Data warehousing, bringing data from multiple sources under a single authority, increases risk of privacy violations. Furthermore, privacy concerns may prevent the parties from directly sharing even some meta-data. Distributed data mining and processing provi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Data Science Journal
سال: 2010
ISSN: 1683-1470
DOI: 10.2481/dsj.008-040