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]