Use a real-life example of an AI system to discuss some impacts of cyber attacks : Grey-Box Adversarial with Example

The video tutorial discusses gray box attacks, focusing on the transferability of adversarial examples between models. It explains how adversarial examples crafted for one model can be used to exploit another, highlighting the importance of testing transferability. The tutorial demonstrates testing transferability between a source model and a target model, showing how different attack methods affect performance. It concludes with lessons on choosing effective attack strategies for better performance on target models.

What is the main idea behind the transferability phenomenon in adversarial attacks?

• Transferability ensures that all models are equally vulnerable.

• Adversarial examples can be transferred between different models.

• Adversarial examples can only be used on the model they were created for.

• Transferability is only effective in black box attacks.

What is the first step in testing transferability between models?

• Changing the attack method.

• Crafting an attack on the target network.

• Training the source neural network.

• Evaluating the performance of the target network.

Why is it important to evaluate the performance of adversarial datasets?

• To verify the accuracy of the source network.

• To compare different neural network architectures.

• To determine the effectiveness of the attack on the target network.

• To ensure the dataset is large enough.

How does the 'Sam' method differ from the 'Wildife full' method in adversarial attacks?

• Sam is a multi-step method, while Wildife full is a single-step method.

• Sam focuses on general perturbations, while Wildife full finds the closest possible change.

• Sam is a fast and simple one-step method, while Wildife full finds more general perturbations.

• Sam is used for black box attacks, while Wildife full is for gray box attacks.

What is the recommended strategy for achieving better performance on target models in transferability attacks?

• Choosing a multi-step attack method.

• Avoiding any changes to the attack method.

• Using a single-step attack method.

• Focusing on the source network's accuracy.