Researchers report a hybrid adversarial domain adaptation method combining logit correlation and gradient randomization that ...

IFAP generates adversarial perturbations using model gradients and then shapes them in the discrete cosine transform (DCT) domain. Unlike existing frequency-aware methods that apply a fixed frequency ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Lily Mara explains how to avoid high-risk ...

The patch only fools a specific algorithm, but researchers are working on more flexible solutions The patch only fools a specific algorithm, but researchers are working on more flexible solutions The ...

Newswise — Robot vision systems are indispensable for autonomous functionalities such as object recognition and navigation, yet they remain highly vulnerable to data poisoning and adversarial attacks.

Louise Matsakis covers cybersecurity, internet law, and online culture for WIRED. Now, a leading group of researchers from MIT have found a different answer, in a paper that was presented earlier this ...

We’ve touched previously on the concept of adversarial examples—the class of tiny changes that, when fed into a deep-learning model, cause it to misbehave. In March, we covered UC Berkeley professor ...

Adversarial machine learning is a technique used in machine learning (ML) to fool or misguide a model with malicious input. While adversarial machine learning can be used in a variety of applications, ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...