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Information privacy

About: Information privacy is a research topic. Over the lifetime, 25412 publications have been published within this topic receiving 579611 citations. The topic is also known as: data privacy & data protection.


Papers
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Journal ArticleDOI
TL;DR: A technique that uses EM mixture modeling to perform clustering on distributed data that controls data sharing, preventing disclosure of individual data items or any results that can be traced to an individual site.
Abstract: Privacy and security considerations can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery can alleviate this problem. We present a technique that uses EM mixture modeling to perform clustering on distributed data. This method controls data sharing, preventing disclosure of individual data items or any results that can be traced to an individual site.

153 citations

Book
01 Jan 2008
TL;DR: This paper first considers privacy and security requirements for e-commerce applications; it then discusses methods and technologies that can be used to fulfil these requirements.
Abstract: Trust, Privacy and Security in Digital Business : Proceedings of the 6th International Conference, TrustBus 2009, Linz, Austria, September 3-4, 2009

153 citations

Proceedings ArticleDOI
01 Jun 2019
TL;DR: Wang et al. as discussed by the authors developed privacy-preserving financial data analytics systems that can detect fraud with high security and accuracy, and they will perform demonstration tests with several financial institutions and solve the problems necessary for their implementation in the real world.
Abstract: We aim at creating a society where we can resolve various social challenges by incorporating the innovations of the fourth industrial revolution (e.g. IoT, big data, AI, robot, and the sharing economy) into every industry and social life. By doing so the society of the future will be one in which new values and services are created continuously, making people's lives more conformable and sustainable. This is Society 5.0, a super-smart society. Security and privacy are key issues to be addressed to realize Society 5.0. Privacy-preserving data analytics will play an important role. In this talk we show our recent works on privacy-preserving data analytics such as privacy-preserving logistic regression and privacy-preserving deep learning. Finally, we show our ongoing research project under JST CREST “AI”. In this project we are developing privacy-preserving financial data analytics systems that can detect fraud with high security and accuracy. To validate the systems, we will perform demonstration tests with several financial institutions and solve the problems necessary for their implementation in the real world.

153 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023562
20221,226
20211,535
20201,634
20191,255
20181,277