Conference
[C2] Qingying Hao, Nirav Diwan, Ying Yuan, Giovanni Apruzzese, Mauro Conti, Gang Wang.
It Doesn't Look Like Anything to Me: Using Diffusion Model to Subvert Visual Phishing Detectors.
In Proceedings of The 33rd USENIX Security Symposium. 2024. (USENIX Security 2024),
Philadelphia, PA, August 14-16, 2024. (Acceptance rate: 18.3%) [Github repo]
[C1] Ying Yuan, Qngying Hao, Apruzzese Giovanni, Mauro Conti, and Gang Wang.
“Are Adversarial Phishing Webpages a Threat in Reality?” Understanding the Users’ Perception of Adversarial Webpages.
In Proceedings of The ACM Web Conference. 2024. (WWW 2024),
Singapore, May 13-17, 2024. (Acceptance rate: 20.2%) [artifacts available] [website]
[C0] Apruzzese Giovanni, Mauro Conti, and Ying Yuan.
SpacePhish: The Evasion-space of Adversarial Attacks against Phishing Website Detectors using Machine Learning.
In Proceedings of the 38th Annual Computer Security Applications Conference. 2022. (ACSAC 2022),
Austin, TX, USA, December 5-9, 2022. (Acceptance rate: 24.1%)[reusable badge][talk]