Use a real-life example of an AI system to discuss some impacts of cyber attacks : Practical Privacy Attacks

The video tutorial introduces privacy attacks, focusing on the membership inference attack using the cipher cat framework. It explains how to determine if specific data was part of a dataset by employing shadow models and attack networks. The tutorial covers the practical steps of loading datasets, training shadow models, and executing the attack, highlighting the transferability of results across datasets. The video concludes with the results of the attack, achieving a 56% accuracy in a black box scenario, and encourages further exploration of the cipher cat library.

What is the primary goal of a membership inference attack?

• To encrypt sensitive data

• To improve model accuracy

• To reduce data redundancy

• To determine if specific data was part of a training dataset

Which framework is mentioned for testing AI solutions against privacy attacks?

• Privacy Shield

• Data Guard

• Cipher Cat

• AI Protector

What is the role of the shadow model in the membership inference attack?

• To improve model efficiency

• To mimic the target network

• To generate classification probability vectors

• To encrypt data

What accuracy did the shadow model achieve during training?

• 75%

• 56%

• 80%

• 99%

What is the significance of transferability in the context of the attack?

• It allows the attack to be applied across different datasets

• It increases the speed of the attack

• It ensures data privacy

• It reduces the complexity of the attack