For providing Big Data privacy, its important that utility of the data/mining result should be preserved. For that before implementing anything, first we need to prove the concept/idea mathematically/theoretically.
Can anyone suggests good Papers/articles/notes on Good Mathematical foundation of Big Data Privacy preserving Models/algorithms?
Also, suggest some open issues in Big Data Privacy/ Privacy Preserving Big Data Analytics.
Hoping for your kind reply.
I suggest checking out the ARX tool, as it does analysis of anonymized data utility, and potential risk under different scenarios using several different mathematical models of anonymization. The authors have published a number of papers on the techniques used there. Check it out here: https://www.researchgate.net/project/ARX-Open-Source-Data-Anonymization-Software
Jeff Sedayao
Thank you for your valuable response...but i have doubt of...is ARX tool can be used for Big Data?? like i have 1TB of structured data...i want to analyze them...
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