Hyperparticle/one-pixel-attack-keras resource
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3119
- days_rel: n/a
- days_push: 861
- n_releases_24m: 0
Adoption not part of the score
1237 stars · 214 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Keras/TensorFlow implementation and tutorial of the 'One Pixel Attack' paper, which fools deep neural networks by modifying a single pixel using differential evolution. It includes Jupyter notebooks demonstrating black-box adversarial attacks on CIFAR-10 and ImageNet classifiers.
Use cases
- generate adversarial examples to fool image classifiers
- learn how differential evolution attacks neural networks
- evaluate robustness of a CNN against one-pixel perturbations
- reproduce the one pixel attack paper in Keras
- study black-box adversarial machine learning attacks
- run adversarial attack experiments on CIFAR-10 in Colab
When to choose
- you want a runnable, educational implementation of the one-pixel attack with notebooks
- you use Keras/TensorFlow and want to test model robustness with a black-box evolutionary attack
- you are studying adversarial machine learning and want to see differential evolution applied to attacks
When to avoid
- you need production-grade adversarial training or defense tooling
- you use PyTorch or need attacks beyond one-pixel perturbations
- you need actively maintained code for the latest TensorFlow versions
Facets
learning-resource · maturity maintenance
machine-learning deep-learning image-processing security machine-learning deep-learning computer-vision security python adversarial-attacks differential-evolution keras tensorflow cifar10 imagenet jupyter-notebook black-box-attack tutorial gpu
6 sources
- readme: https://github.com/Hyperparticle/one-pixel-attack-keras · fetched 2026-08-28 · cebb533e270a
- homepage: https://arxiv.org/abs/1710.08864 · fetched 2026-08-29 · 4c9dc1b54dce
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Hyperparticle/one-pixel-attack-keras | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="Hyperparticle/one-pixel-attack-keras")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem