adversarial-robustness-toolbox
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Added support for SNAL attack
Description
This pull request adds the support of the SNAL Attack proposed in [1].
[1]Steal Now and Attack Later: Evaluating Robustness of Object Detection against Black-box Adversarial Attacks. [Paper] Fixes # (issue)
Type of change
Please check all relevant options.
- [ ] Improvement (non-breaking)
- [ ] Bug fix (non-breaking)
- [X] 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
Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.
- [X] Notebook Example
Test Configuration:
- OS: Ubuntu 20.04
- Python version: 3.8.12
- ART version or commit number: 900f4700
- PyTorch version: 1.13.1+cu116
- cudnn version: 8302
Checklist
- [X] My code follows the style guidelines of this project
- [X] I have performed a self-review of my own code
- [X] I have commented my code
- [X] I have made corresponding changes to the documentation
- [X] My changes generate no new warnings
- [X] I have added tests that prove my fix is effective or that my feature works
- [X] New and existing unit tests pass locally with my changes
- [X] My changes have been tested using both CPU and GPU devices
Codecov Report
Attention: Patch coverage is 89.65517%
with 48 lines
in your changes missing coverage. Please review.
Project coverage is 85.31%. Comparing base (
7983374
) to head (ce3aec7
).
Additional details and impacted files
@@ Coverage Diff @@
## dev_1.19.0 #2440 +/- ##
==============================================
+ Coverage 85.25% 85.31% +0.06%
==============================================
Files 330 333 +3
Lines 30470 30930 +460
Branches 5228 5294 +66
==============================================
+ Hits 25977 26388 +411
- Misses 3042 3074 +32
- Partials 1451 1468 +17
Files with missing lines | Coverage Δ | |
---|---|---|
art/attacks/evasion/__init__.py | 100.00% <100.00%> (ø) |
|
...attacks/evasion/steal_now_attack_later/bbox_ioa.py | 100.00% <100.00%> (ø) |
|
art/estimators/object_detection/pytorch_yolo.py | 87.23% <ø> (ø) |
|
...mators/object_detection/pytorch_object_detector.py | 89.44% <84.61%> (-0.56%) |
:arrow_down: |
...cks/evasion/steal_now_attack_later/drop_block2d.py | 75.00% <75.00%> (ø) |
|
...n/steal_now_attack_later/steal_now_attack_later.py | 90.14% <90.14%> (ø) |