activity
20222026
most citedWild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples

20 citations · 48 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CR20251 cited

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…

cs.CR20254 cited

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…

cs.SE20252 cited

"We provide our resources in a dedicated repository": Surveying the Transparency of HICSS publications

Irdin Pekaric, Giovanni Apruzzese

Every day, new discoveries are made by researchers from all across the globe and fields. HICSS is a flagship venue to present and discuss such scientific advances. Yet, the activit…

cs.CR202514 cited

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…

cs.CR20251 cited

The Ephemeral Threat: Assessing the Security of Algorithmic Trading Systems powered by Deep Learning

Advije Rizvani, Giovanni Apruzzese, Pavel Laskov

We study the security of stock price forecasting using Deep Learning (DL) in computational finance. Despite abundant prior research on the vulnerability of DL to adversarial pertur…

cs.HC202416 cited

LLM4PM: A case study on using Large Language Models for Process Modeling in Enterprise Organizations

Clara Ziche, Giovanni Apruzzese

We investigate the potential of using Large Language Models (LLM) to support process model creation in organizational contexts. Specifically, we carry out a case study wherein we d…