Finding classifiers robust to adversarial examples is critical for their...
Recent text-to-image diffusion models such as MidJourney and Stable Diff...
Today, creators of data-hungry deep neural networks (DNNs) scour the Int...
Extensive literature on backdoor poison attacks has studied attacks and
...
Backdoors are powerful attacks against deep neural networks (DNNs). By
p...
Server breaches are an unfortunate reality on today's Internet. In the
c...
In deep neural networks for facial recognition, feature vectors are nume...
The rapid adoption of facial recognition (FR) technology by both governm...
In adversarial machine learning, new defenses against attacks on deep
le...
Advances in deep learning have introduced a new wave of voice synthesis
...
Edge video analytics is becoming the solution to many safety and managem...
Anonymity systems like Tor are vulnerable to Website Fingerprinting (WF)...
Backdoor attacks embed hidden malicious behaviors inside deep neural net...
The vulnerability of deep neural networks (DNNs) to adversarial examples...
Today's proliferation of powerful facial recognition models poses a real...
Despite continuous efforts to build and update network infrastructure, m...
Accurate traffic speed prediction is an important and challenging topic ...
As deep learning classifiers continue to mature, model providers with
su...
Recent work has proposed the concept of backdoor attacks on deep neural
...
Deep neural networks are vulnerable to adversarial attacks. Numerous eff...
Recent works have explained the principle of using ultrasonic transmissi...
Millimeter-wave wireless networks offer high throughput and can (ideally...
Wireless devices are everywhere, at home, at the office, and on the stre...
Wireless devices are everywhere, at home, at the office, and on the stre...
Deep learning is often constrained by the lack of large, diverse labeled...