Anonymiser
This is a guide to how to use the anonymiser component of the PISTIS Platform
Home Page
- Displays the first five rows of a dataset as a preview of the what the newly transformed dataset will look like
- "Apply Button" when clicked the transformed dataset stored in the anonymiser will be submitted to the factory data components to be saved and lineage will be created
- "Discard Changes" button will delete the dataset from the anonymiser and return the user to the pistis platform home page
- You can navigate to tools to obfuscate the dataset using the "Obfuscate Utilities" button or the "Obfuscation" link at the top of the page
- You can navigate to tools for applying kanonymity to the dataset using the "k-Anonymity" button or the "k-Anonymity" link at the top of the page
- This page also displays which columns were deemed sensitive by the anonymiser under "Sensitivity Report"
Data Obfuscation Page 1
- Shows a preview of what the dataset currently stored in the anonymiser looks like and some "Obfuscation Settings"
- Under the "Obfuscation Settings" you can configure how you would like the anonymiser to transform the dataset
- There are five different types of transformations that can be chosen in the obfuscation settings menu: faker, range, hash, location, delete
- faker will replace a column with believable values of a chosen category. You choose this category from a drop down menu in the column's settings.
- range will replace each number in the column with a range in which that number falls. You choose how big this range is from a drop down menu in the column's settings.
- hash will replace a value with a syntax preserving hash
- location will replace a latitude and longitude column with generated values that preserve statistical properties
- delete will delete the column
- click the "Preview Transformation" to preview the effect that this will have on the dataset
Data Obfuscation Page 2
- The transformation preview of the obfuscation page is only shown once the "Preview Transformation" button is clicked.
- click the "Apply Transformation" if you are happy with the transformation to save the changes to the instance of the dataset stored in the anonymiser (not to the factory data store)
K-Anonymity Page 1
- kanonymity page for the anonymiser
- Shows a preview of the dataset currently store in the anonymiser and some "Sensitivity Settings"
- "Sensitivity Settings" shows the sensitivity of each column as determined by the anonymiser
- Click the "See Solutions'' button to generate a list of potential configurations (known as solutions) that can be applied to the dataset to render it anonymous
K-Anonymity Page 2
- shows the solutions menu of the kanonymity page for the anonymiser. This only appears once "See Solutions'' is clicked.
- Under "Solutions'' you will see a list of solutions
- In the solutions table each row shows a single solution and details the effect the solution will have on the dataset as well as the estimated information loss that the application of this solution will result in
- Click the "Preview" button next to a to preview the effect a solution will have on the dataset
K-Anonymity Page 3
- Shows the preview of the transformed dataset of the kanonymity page for the anonymiser. This only appears once "Preview'' is clicked.
- Under "Preview" you will see a preview of the effect the solution had
- If you are happy with the result of the anonymisation then click the "Anonymize Dataset" button to save the changes to the instance of the dataset stored in the anonymiser (not to the factory data store)
Synthetic Data Generation Page 1
- Synthetic Data Generator page for the anonymiser
- Shows a preview of the dataset currently store in the anonymiser
- Press the 'Replace Data' Button to generate a replacement dataset for the original dataset
