Privacy preservation algorithm in data mining for CRM systems

Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy pro...

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Bibliographic Details
Main Authors: Virupaksha, Shashidhar, Sahoo, G., Vasudevan, Ananthasayanam
Format: Conference Proceeding
Language:English
Subjects:
Clustering algorithms
Data privacy
Diseases
Privacy
Remuneration
Online Access:Request full text
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Summary:Organizations have a huge customer base and thus they use data mining tools to study their customers. However there is risk of sensitive information about individuals which can be gained also during this process. Hence data that is used for data mining has to be protected. There are some privacy protection algorithms which ensure privacy and protect data. These algorithms preserve privacy but data mining results significantly. In this paper we propose a clustering based noise addition that not only preserves privacy but also ensures effective data mining. Data characteristics are identified using clustering technique and noise is added within the clusters thus retaining the data characteristics.
DOI:10.1109/ICCSP.2014.6950121