On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining
Additive Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining. The previous work based on Spectral Filtering empirically showed that individual data can be separated from the perturbed one and as a result privacy can be seriously compromis...
محفوظ في:
المؤلفون الرئيسيون: | GUO, Songtao, Wu, Xintao, LI, Yingjiu |
---|---|
التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2006
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/322 http://dx.doi.org/10.1007/11871637_51 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Determining Error Bounds for Spectral Filtering Based Reconstruction Methods in Privacy Preserving Data Mining
بواسطة: GUO, Songtao, وآخرون
منشور في: (2008) -
Preserving Privacy in Association Rule Mining with Bloom Filters
بواسطة: QIU, Ling, وآخرون
منشور في: (2007) -
Protecting business intelligence and customer privacy while outsourcing data mining tasks
بواسطة: QIU, Ling, وآخرون
منشور في: (2008) -
An Approach to Outsourcing Data Mining Tasks While Protecting Business Intelligence and Customer Privacy
بواسطة: QU, Ling, وآخرون
منشور في: (2006) -
Deriving Private Information from Perturbed Data using IQR Based Approach
بواسطة: GUO, Songtao, وآخرون
منشور في: (2006)