14 citations · 39 across the 10 of their papers we have counts for
9 papers · 1 filter
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…
It's not Easy: Applying Supervised Machine Learning to Detect Malicious Extensions in the Chrome Web Store
Ben Rosenzweig, Valentino Dalla Valle, Giovanni Apruzzese +1
Google Chrome is the most popular Web browser. Users can customize it with extensions that enhance their browsing experience. The most well-known marketplace of such extensions is…
E-PhishGen: Unlocking Novel Research in Phishing Email Detection
Luca Pajola, Eugenio Caripoti, Stefan Banzer +3
Every day, our inboxes are flooded with unsolicited emails, ranging between annoying spam to more subtle phishing scams. Unfortunately, despite abundant prior efforts proposing sol…
Misleading Large Language Models used (or misused) in Scientific Peer-Reviewing via Hidden Prompt-Injection Attacks
Matteo Gioele Collu, Umberto Salviati, Roberto Confalonieri +2
Large Language Models (LLMs) are increasingly being integrated into the scientific peer-review process, raising new questions about their reliability and resilience to manipulation…
The Impact of Emerging Phishing Threats: Assessing Quishing and LLM-generated Phishing Emails against Organizations
Marie Weinz, Nicola Zannone, Luca Allodi +1
Modern organizations are persistently targeted by phishing emails. Despite advances in detection systems and widespread employee training, attackers continue to innovate, posing on…
SoK: On the Offensive Potential of AI
Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human +13
Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revea…