Adversarial Attacks Explained
Attackers are increasingly targeting machine learning systems, particularly through cloud APIs that assess content safety. By utilizing black box attacks and transferability techniques, it's possible to create local models that can effectively deceive remote models, even without knowledge of their architecture or parameters. Recent studies have expanded this research from computer vision to natural language processing, showcasing the vulnerabilities in systems like machine translation.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
AI and the Responsible Data Economy with Dawn Song - #403
Related Questions
What are adversarial attacks on machine learning models as discussed in the episode Dawn Song: Adversarial Machine Learning and Computer Security | Lex Fridman Podcast #95 and the clip Real World Vulnerabilities?
Can you give examples of adversarial attacks on machine learning models?
What are adversarial attacks on machine learning models?