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Introducing AdversaNet
Introducing AdversaNet
Understand and Visualize
How AI Can Be Fooled?
Our interactive dashboard helps you explore adversarial attacks on image classifiers. Upload images, apply attacks like FGSM and PGD, and see how even small changes can trick powerful AI models—making it easier to learn, teach, and build more secure systems.
✶Introduction
Understanding vulnerabilities is the first step to building robust AI. AI systems are increasingly being adopted in critical applications, yet many remain vulnerable to subtle, adversarial manipulations—often invisible to the human eye but highly disruptive to machine learning models. That’s why we built AdversaNet.
✶Platform Features
Explore Adversarial Vulnerabilities in AI
Interactive Dashboard for Adversarial Attacks
Visualize the effect of adversarial perturbations on image classifiers. Upload images and apply attacks like FGSM, PGD, and DeepFool in real-time.
What
changed in the prediction?
Confidence Scores & Model Predictions
Compare how model predictions and confidence scores shift before and after attacks. Great for learning and debugging AI behavior.
Customizable Attack Parameters
Modify parameters like epsilon or iteration steps and see how they affect the success of attacks. Helps users grasp sensitivity and model robustness.
✶Upload Custom or Sample Images
✶Apply FGSM, PGD, BIM Attacks
✶View Original vs. Perturbed Images
✶Model Confidence Score Charts
✶Visual Perturbation Heatmaps
✶Toggle Visualization Layers
✶Interactive Parameter Controls
✶Pricing
Flexible Plans for Researchers, Educators & ML Teams
✶FAQs