3 citations · 4 across the 3 of their papers we have counts for
3 papers
"Do Users fall for Real Adversarial Phishing?" Investigating the Human response to Evasive Webpages
Ajka Draganovic, Savino Dambra, Javier Aldana Iuit +2
Phishing websites are everywhere, and countermeasures based on static blocklists cannot cope with such a threat. To address this problem, state-of-the-art solutions entail the appl…
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
Giovanni Apruzzese, Hyrum S. Anderson, Savino Dambra +3
Recent years have seen a proliferation of research on adversarial machine learning. Numerous papers demonstrate powerful algorithmic attacks against a wide variety of machine learn…
Collaborative and Privacy-Preserving Machine Teaching via Consensus Optimization
Yufei Han, Yuzhe Ma, Christopher Gates +2
In this work, we define a collaborative and privacy-preserving machine teaching paradigm with multiple distributed teachers. We focus on consensus super teaching. It aims at organi…