TAD: Trigger Approximation based Black-box Trojan Detection for AI

Understand

An emerging amount of intelligent applications have been developed with the surge of Machine Learning (ML).

• Deep Neural Networks (DNNs) have demonstrated unprecedented performance across various fields such as medical diagnosis and autonomous driving.
• While DNNs are widely employed in security-sensitive fields, they are identified to be vulnerable to Neural Trojan (NT) attacks that are controlled and activated by the stealthy trigger.
• We call this vulnerable model adversarial artificial intelligence (AI).