Privacy-preserving collaborative data mining
نویسندگان
چکیده
منابع مشابه
Privacy Preserving Data Mining
Through data mining collect large amount of data in many organizations. A key value of huge databases today is technical or financial research. In a huge collection of data there arises a key issue that is privacy. Due to personal interests, medical databases or business interests privacy is needed. Due to privacy infringement while performing the data mining operations this is often not possib...
متن کاملPrivacy Preserving Data Mining
Recent interest in data collection and monitoring using data mining for security and business-related applications has raised privacy. Privacy Preserving Data Mining (PPDM) techniques require data modification to disinfect them from sensitive information or to anonymize them at an uncertainty level. This study uses PPDM with adult dataset to investigate effects of K-anonymization for evaluation...
متن کاملPrivacy Preserving Data Mining
There is a tremendous increase in the research of data mining. Data mining is the process of extraction of data from large database. Knowledge Discovery in database (KDD) is another name of data mining. Privacy protection has become a necessary requirement in many data mining applications due to emerging privacy legislation and regulations. One of the most important topics in research community...
متن کاملPrivacy Preserving Data Mining
The problem of secure distributed classification is an important one. In many situations, data is split between multiple organizations. These organizations may want to utilize all of the data to create more accurate predictive models while revealing neither their training data / databases nor the instances to be classified. The Naive Bayes Classifier is a simple but efficient baseline classifie...
متن کاملPrivacy-Preserving Data Mining
Privacy-preserving data mining (PPDM) refers to the area of data mining that seeks to safeguard sensitive information from unsolicited or unsanctioned disclosure. Most traditional data mining techniques analyze and model the data set statistically, in aggregation, while privacy preservation is primarily concerned with protecting against disclosure individual data records. This domain separation...
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ژورنال
عنوان ژورنال: IEEE Computational Intelligence Magazine
سال: 2008
ISSN: 1556-603X
DOI: 10.1109/mci.2008.919071