14 citations · 39 across the 10 of their papers we have counts for
11 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…
X-raying the arXiv: A Large-Scale Analysis of arXiv Submissions' Source Files
Giovanni Apruzzese, Aurore Fass
arXiv is the largest open-access repository for scientific literature. When submitting a paper, authors upload the manuscript's source files, from which the final PDF is compiled.…
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…
Elephant in the Room: Dissecting and Reflecting on the Evolution of Online Social Network Research
Luca Pajola, Saskia Laura Schröer, Pier Paolo Tricomi +2
Billions of individuals engage with Online Social Networks (OSN) daily. The owners of OSN try to meet the demands of their end-users while complying with business necessities. Such…
"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…
Understanding the Process of Data Labeling in Cybersecurity
Tobias Braun, Irdin Pekaric, Giovanni Apruzzese
Many domains now leverage the benefits of Machine Learning (ML), which promises solutions that can autonomously learn to solve complex tasks by training over some data. Unfortunate…
"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…