Support scaling input features to attacks

[abigailgold]

Description

Both black-box membership inference and black-box attribute inference can scale input features to the attack using multiple options of sciki-learn scalers (default is StandardScaler).

Fixes #2152

Type of change

Please check all relevant options.

• Improvement (non-breaking)
• Bug fix (non-breaking)
• New feature (non-breaking)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Testing

New tests that try out all options for scaling.

Test Configuration:

• OS: MacOS 14.2.1
• Python version: 3.9
• ART version or commit number
• TensorFlow / Keras / PyTorch / MXNet version

Checklist

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• My changes have been tested using both CPU and GPU devices

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 78.84615% with 11 lines in your changes are missing coverage. Please review.

Project coverage is 85.52%. Comparing base (3597228) to head (290519d).

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Additional details and impacted files

@@              Coverage Diff               @@
##           dev_1.18.0    #2384      +/-   ##
==============================================
- Coverage       85.54%   85.52%   -0.02%     
==============================================
  Files             327      327              
  Lines           29888    29937      +49     
  Branches         5528     5546      +18     
==============================================
+ Hits            25567    25604      +37     
- Misses           2900     2905       +5     
- Partials         1421     1428       +7     

Files	Coverage Δ
...attacks/inference/attribute_inference/black_box.py	89.62% <87.50%> (-0.14%)	⬇️
...ttacks/inference/membership_inference/black_box.py	88.71% <75.00%> (-1.79%)	⬇️

... and 3 files with indirect coverage changes

[beat-buesser]

Hi @abigailgold Thank you very much! It looks good to me.