adversarial backdoor
Scientists found a way to plug adversarial backdoors in deep learning models
Imagine a high-security complex protected by a facial recognition system powered by deep learning. The artificial intelligence algorithm has been tuned to unlock the doors for authorized personnel only, a convenient alternative to fumbling for your keys at every door. A stranger shows up, dons a bizarre set of spectacles, and all of a sudden, the facial recognition system mistakes him for the company's CEO and opens all the doors for him. By installing a backdoor in the deep learning algorithm, the malicious actor ironically gained access to the building through the front door. This is not a page out of a sci-fi novel.
Adversarial AI: Blocking the hidden backdoor in neural networks
This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Imagine a high-security complex protected by a facial recognition system powered by deep learning. The artificial intelligence algorithm has been tuned to unlock the doors for authorized personnel only, a convenient alternative to fumbling for your keys at every door. A stranger shows up, dons a bizarre set of spectacles, and all of a sudden, the facial recognition system mistakes him for the company's CEO and opens all the doors for him. By installing a backdoor in the deep learning algorithm, the malicious actor ironically gained access to the building through the front door.