Icon

Challenge 9 - Simple Anonymization - Aline

You would like to post a question on the KNIME forum, but you have confidential data that you cannot share. In this challenge you will create a workflow which removes (or transforms) any columns that reveal anything confidential in your data (such as location, name, gender, etc.). After that, you should shuffle the remaining columns' rows such that each numeric column maintains its original statistical distribution but does not have a relationship with any other column. Rename these columns as well, such that in the end of your workflow they do not have any specific meaning. Let's see an example:

Example:
BEFORE ANONYMIZATION
Row Name Fav_Num Muscle_Mass
0 Victor 7 10
1 Aline 3 20
2 Scott 42 30

AFTER ANONYMIZATION
Row column column (#1)
0 3 30
1 42 10
2 7 20

Feel free to see our resources on data anonymization for inspiration (https://www.knime.com/blog/data-anonymization-in-knime-a-redfield-privacy-extension-walkthrough) , but note that the task here is much simpler! For reference, our solution only uses 7 nodes to anonymize and 3 additional nodes to do make sure the data truly was anonymized.

You would like to post a question on the KNIME forum, but you have confidential data that you cannot share. In this challenge you will create a workflow which removes (or transforms) any columns thatreveal anything confidential in your data (such as location, name, gender, etc.). After that, you should shuffle the remaining columns' rows such that each numeric column maintains its original statisticaldistribution but does not have a relationship with any other column. Rename these columns as well, such that in the end of your workflow they do not have any specific meaning. Let's see an example:Example:BEFORE ANONYMIZATIONRow Name Fav_Num Muscle_Mass0 Victor 7 101 Aline 3 202 Scott 42 30AFTER ANONYMIZATIONRow column column (#1)0 3 301 42 102 7 20Feel free to see our resources on data anonymization for inspiration (https://www.knime.com/blog/data-anonymization-in-knime-a-redfield-privacy-extension-walkthrough) , but note that the task here ismuch simpler! For reference, our solution only uses 7 nodes to anonymize and 3 additional nodes to do make sure the data truly was anonymized. Read fifa datasetRemove sensitivecolumnsShuffle columnsloop overremaining columnscollect shuffled columnsCreate new RowIDsReplace old RowIDswith new onesrename columnscolumn correlationsbefore shufflingcolumn correlationsafter shuffling;note how they changed!comparing before and after row by row CSV Reader Column Filter Shuffle Column ListLoop Start Loop End (ColumnAppend) RowID Column Filter Column Rename(Regex) Linear Correlation Linear Correlation Table DifferenceFinder You would like to post a question on the KNIME forum, but you have confidential data that you cannot share. In this challenge you will create a workflow which removes (or transforms) any columns thatreveal anything confidential in your data (such as location, name, gender, etc.). After that, you should shuffle the remaining columns' rows such that each numeric column maintains its original statisticaldistribution but does not have a relationship with any other column. Rename these columns as well, such that in the end of your workflow they do not have any specific meaning. Let's see an example:Example:BEFORE ANONYMIZATIONRow Name Fav_Num Muscle_Mass0 Victor 7 101 Aline 3 202 Scott 42 30AFTER ANONYMIZATIONRow column column (#1)0 3 301 42 102 7 20Feel free to see our resources on data anonymization for inspiration (https://www.knime.com/blog/data-anonymization-in-knime-a-redfield-privacy-extension-walkthrough) , but note that the task here ismuch simpler! For reference, our solution only uses 7 nodes to anonymize and 3 additional nodes to do make sure the data truly was anonymized. Read fifa datasetRemove sensitivecolumnsShuffle columnsloop overremaining columnscollect shuffled columnsCreate new RowIDsReplace old RowIDswith new onesrename columnscolumn correlationsbefore shufflingcolumn correlationsafter shuffling;note how they changed!comparing before and after row by rowCSV Reader Column Filter Shuffle Column ListLoop Start Loop End (ColumnAppend) RowID Column Filter Column Rename(Regex) Linear Correlation Linear Correlation Table DifferenceFinder

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: alinebessa
Created at: 2022-03-25
On NodePit since: 2022-03-25
Last update: 2024-04-27
Created with KNIME version: v4.5.1
Tags: justknimeit-9justknimeitdata-anonymization

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!