Loading…
Privacy Preserving Unstructured Big Data Analytics: Issues and Challenges
Big data analytics has created opportunities for researchers to process huge amount of data but created a big threat to privacy of individual. Data processed by big data analytics platforms may have personal information which need to be taken care of when deriving some useful results for research. E...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Big data analytics has created opportunities for researchers to process huge amount of data but created a big threat to privacy of individual. Data processed by big data analytics platforms may have personal information which need to be taken care of when deriving some useful results for research. Existing privacy preserving techniques like, anonymization requires having dataset divided in the set of attributes like, sensitive attributes, quasi identifiers, and non-sensitive attributes. With the structured data it may possible to have such a distribution but in unstructured data it is very difficult to identify sensitive attribute and quasi identifiers. |
---|---|
ISSN: | 1877-0509 1877-0509 |
DOI: | 10.1016/j.procs.2016.02.020 |