Currently, several privacy preservation methods for data mining are available. These include K-anonymity, classification, clustering, association rule, distributed privacy preservation, L-diverse, randomization, taxonomy tree, condensation, and cryptographic (Sachan et al. 2013).
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Nov 12, 2021 · Data mining can help a company detect instances of fraud and take action. For example, data mining can flag fake or suspicious social media ...
Aug 12, 2024 · Data mining security helps safeguard mined data from unauthorized access, alteration, or disclosure throughout the mining process.
Oct 6, 2023 · To protect privacy, data mining should be conducted with transparency and consent. Implementing strict data protection regulations, like GDPR, ...
Nov 12, 2015 · Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data ...
The need for privacy is sometimes due to law (e.g., for medical databases) or can be motivated by business interests.
May 30, 2023 · Data mining collects and analyzes mountains of your personal information and behavior to find patterns and sell you goods and services.
May 4, 2023 · Privacy concerns: Data mining can raise privacy concerns, as it involves collecting and analyzing data about individuals without their explicit ...
Privacy-Preserving Data Mining: Models and Algorithms
Book
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. ... Google Books
Originally published: June 10, 2008
This paper provides a framework and metrics for discussing the meaning of privacy preserving data mining, as a foundation for further research in this field. 1.
Oct 22, 2024 · In this paper, we view the privacy issues related to data mining from a wider perspective and investigate various approaches that can help to protect sensitive ...