6 papers
Improving Generalization on Cybersecurity Tasks with Multi-Modal Contrastive Learning
Jianan Huang, Rodolfo V. Valentim, Luca Vassio +4
The use of ML in cybersecurity has long been impaired by generalization issues: Models that work well in controlled scenarios fail to maintain performance in production. The root c…
Towards Agentic Honeynet Configuration
Federico Mirra, Matteo Boffa, Idilio Drago +2
Honeypots are deception systems that emulate vulnerable services to collect threat intelligence. While deploying many honeypots increases the opportunity to observe attacker behavi…
The Potential of Erroneous Outbound Traffic Analysis to Unveil Silent Internal Anomalies
Andrea Sordello, Zhihao Wang, Kai Huang +2
Passive measurement has traditionally focused on inbound traffic to detect malicious activity, based on the assumption that threats originate externally. In this paper, we offer a…
Analyzing BEV Suitability and Charging Strategies Using Italian Driving Data
Homa Jamalof, Luca Vassio, Danilo Giordano +2
Battery Electric Vehicles (BEVs) are rapidly evolving from a niche alternative to an established option for private transportation, often replacing Internal Combustion Engine (ICE)…
CyberSleuth: Autonomous Blue-Team LLM Agent for Web Attack Forensics
Stefano Fumero, Kai Huang, Matteo Boffa +3
Post-mortem analysis of compromised systems is a key aspect of cyber forensics, today a mostly manual, slow, and error-prone task. Agentic AI, i.e., LLM-powered agents, is a promis…
Generic Multi-modal Representation Learning for Network Traffic Analysis
Luca Gioacchini, Idilio Drago, Marco Mellia +2
Network traffic analysis is fundamental for network management, troubleshooting, and security. Tasks such as traffic classification, anomaly detection, and novelty discovery are fu…