output
20212026
most citedModeling Realistic Adversarial Attacks against Network Intrusion Detection Systems

144 citations

16 papers

cs.CR2026

Propagation Model for SSC attacks: Why SBOM (tools) don't tell the whole truth

Ljubica Grgic, Lazar Maksimovic, Pavel Laskov

Ensuring security of software supply chains (SSC) is indispensable in today's world of modern software practices. SBOM (tools) have been introduced as relevant building blocks to e…

cs.CR20261 cited

"What is the Problem Space?" Defining Host-space Adversarial Perturbations against Network Intrusion Detection Systems

Miel Verkerken, Laurens D'hooge, Bruno Volckaert +2

Network Intrusion Detection Systems (NIDS) are now increasingly leveraging Machine Learning (ML) techniques to detect malicious network activities. Numerous papers have scrutinized…

cs.CR2026

SoK: Reshaping Research on Network Intrusion Detection Systems

Giovanni Apruzzese

Network Intrusion Detection Systems (NIDS) have been studied for decades. Hundreds of papers have, e.g., proposed ways to enhance, harden or bypass NIDS. However, the findings of p…

cs.CR2026

Adversarial News and Lost Profits: Manipulating Headlines in LLM-Driven Algorithmic Trading

Advije Rizvani, Giovanni Apruzzese, Pavel Laskov

Large Language Models (LLMs) are increasingly adopted in the financial domain. Their exceptional capabilities to analyse textual data make them well-suited for inferring the sentim…

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…