35 citations · 46 across the 3 of their papers we have counts for
3 papers
I can't recognize (yet): Delayed Rendering to Defeat Visual Phishing Detectors
Ying Yuan, Cristiano Alex Rado, Giovanni Apruzzese +2
Phishing webpages are continuously polluting the Web. Plenty of countermeasures have been proposed and the most advanced techniques leverage machine-learning methods that infer whe…
"Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages
Ying Yuan, Qingying Hao, Giovanni Apruzzese +2
Machine learning based phishing website detectors (ML-PWD) are a critical part of today's anti-phishing solutions in operation. Unfortunately, ML-PWD are prone to adversarial evasi…
Multi-SpacePhish: Extending the Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning
Ying Yuan, Giovanni Apruzzese, Mauro Conti
Existing literature on adversarial Machine Learning (ML) focuses either on showing attacks that break every ML model, or defenses that withstand most attacks. Unfortunately, little…