4 papers
Dense Contexts Are Hard Contexts: Lexical Density Limits Effective Context in LLMs
Giovanni Dettori, Matteo Boffa, Danilo Giordano +2
Input length and the position of relevant information are widely cited as the primary causes of degraded LLM long-context performance. Here, we study lexical density -- the rate at…
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…
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…
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)…