AdvEx is an interactive multi-level visualization system designed to help novice machine learning learners understand adversarial evasion attacks in image classification models. The system visualizes subtle, human-imperceptible perturbations used in attacks and allows users to explore their impact across different classifiers, attack methods, and individual images. By supporting multi-level visual exploration — both instance-level and dataset-level — AdvEx highlights how adversarial attacks affect models differently depending on the data, model architecture, and training methods.

Core Features
• Interactive Visualization of Adversarial Evasion Attacks (e.g., FGSM, PGD, ZOO attacks)
• Real-time data analytics and model performance evaluation
• Illustrates the logic and impact of adversarial attacks through dynamic and interactive visualizations

• SkillsPython, PyTorch, scikit-learn, Machine Learning, Evasion Attacks, D3.js, JavaScript, HTML, CSS
• Team MembersYuzhe You, Jarvis Tse, Jian Zhao
• KeywordsHCI, Information Visualization, Adversarial Machine Learning, FGSM, PGD, Model Robustness, HTML, CSS