AI & Security (Adversarial ML Overview)

Summary

AI/ML systems introduce new attack surfaces — adversarial inputs designed to fool a model, data poisoning during training, and AI being used offensively (e.g. more convincing phishing) or defensively (anomaly detection).

• 1Read a conceptual overview of an adversarial example fooling an image classifier.
• 2Learn how AI is increasingly used both offensively (phishing, deepfakes) and defensively (anomaly detection).
• 3Understand this as an emerging, fast-moving area worth continued attention beyond this roadmap.