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 significance of adversarial attacks in model training?

How does the accuracy of the trained model compare to the original model?

What is thermometer encoding and how does it affect model accuracy?

What observations were made regarding the model's performance on normal examples?

What will be compared in the next video according to the text?