Evaluate the impact of privacy issues, cyberattacks, and malware on your AI application : Testing Practical Defence from

The video discusses methods to strengthen models against adversarial attacks, focusing on region-based classification (cotac) and thermometer encoding. It evaluates model parameters, noting improvements in accuracy and defense effectiveness. A comparative analysis of defenses is previewed for the next video.

What is the primary goal of modifying the model as discussed in the first section?

• To reduce the model's size

• To make adversarial attacks easier

• To make adversarial attacks more difficult

• To improve the model's speed

What is the savvy value mentioned in the context of region-based classification?

• Almost one

• Almost zero

• Exactly one

• Exactly zero

Which defense mechanism is introduced in the second section?

• Region-based classification

• Model reduction

• Thermometer encoding

• Savvy encoding

How does the thermometer encoding defense affect the model's accuracy on normal examples?

• It improves the accuracy

• It makes the model less accurate

• It has no effect

• It decreases the accuracy

What is the next step mentioned at the end of the video?

• To finalize the current model

• To implement a new defense

• To compare the defenses in the next video

• To discard the current defenses