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README.md
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---
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license: mit
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tags:
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- adversarial-robustness
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- cifar10
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- pytorch
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- ibm-art
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---
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# Assignment 5 – Adversarial Attacks & Detection (Q2)
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## Overview
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- **ResNet-18** trained from scratch on CIFAR-10 (≥ 72% clean accuracy).
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- **FGSM** attack implemented from scratch and via IBM ART.
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- **ResNet-34** binary detectors trained on PGD and BIM adversarial examples.
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## Checkpoints
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| File | Description |
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|------|-------------|
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| `checkpoints/resnet18_cifar10_best.pth` | Best ResNet-18 classifier |
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| `checkpoints/detector_pgd.pth` | ResNet-34 PGD detector |
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| `checkpoints/detector_bim.pth` | ResNet-34 BIM detector |
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## Results
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See `results/` folder and the WandB project linked in the GitHub README.
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