AI — Security

Security Threats

Threat	Description
Adversarial attacks	Manipulate inputs
Data poisoning	Corrupt training
Model stealing	Extract model
Privacy attacks	Extract data

Adversarial Attacks

import numpy as np

def fgsm_attack(model, image, label, epsilon=0.1):
    image_tensor = tf.convert_to_tensor(image)
    with tf.GradientTape() as tape:
        tape.watch(image_tensor)
        prediction = model(image_tensor)
        loss = loss_fn(label, prediction)
    
    gradient = tape.gradient(loss, image_tensor)
    perturbation = epsilon * tf.sign(gradient)
    adversarial_image = image_tensor + perturbation
    return adversarial_image

Defense Techniques

Defense	Description
Adversarial training	Train on attacks
Input validation	Check inputs
Model watermarking	Protect IP
Differential privacy	Protect data

Mini Practice

1. Understand security threats
2. Create adversarial examples
3. Implement defenses
4. Test model robustness

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