Zobrazeno 1 - 10
of 425
pro vyhledávání: '"Mellia, Marco"'
Autor:
Gioacchini, Luca, Mellia, Marco, Drago, Idilio, Delsanto, Alexander, Siracusano, Giuseppe, Bifulco, Roberto
Generative AI agents, software systems powered by Large Language Models (LLMs), are emerging as a promising approach to automate cybersecurity tasks. Among the others, penetration testing is a challenging field due to the task complexity and the dive
Externí odkaz:
http://arxiv.org/abs/2410.03225
Autor:
Perlo, Alessandro, Paoletti, Giordano, Jha, Nikhil, Vassio, Luca, Almeida, Jussara, Mellia, Marco
Although currently one of the most popular instant messaging apps worldwide, Telegram has been largely understudied in the past years. In this paper, we aim to address this gap by presenting an analysis of publicly accessible groups covering discussi
Externí odkaz:
http://arxiv.org/abs/2409.02525
In the context of cybersecurity, tracking the activities of coordinated hosts over time is a daunting task because both participants and their behaviours evolve at a fast pace. We address this scenario by solving a dynamic novelty discovery problem w
Externí odkaz:
http://arxiv.org/abs/2405.10545
Network traffic analysis is fundamental for network management, troubleshooting, and security. Tasks such as traffic classification, anomaly detection, and novelty discovery are fundamental for extracting operational information from network data and
Externí odkaz:
http://arxiv.org/abs/2405.02649
In response to growing concerns about user privacy, legislators have introduced new regulations and laws such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) that force websites to obtain user consent b
Externí odkaz:
http://arxiv.org/abs/2402.18321
Publikováno v:
4th Workshop on Graphs and more Complex structures for Learning and Reasoning (GCLR) at AAAI 2024
In dynamic complex networks, entities interact and form network communities that evolve over time. Among the many static Community Detection (CD) solutions, the modularity-based Louvain, or Greedy Modularity Algorithm (GMA), is widely employed in rea
Externí odkaz:
http://arxiv.org/abs/2312.13784
Sound-squatting is a phishing attack that tricks users into malicious resources by exploiting similarities in the pronunciation of words. Proactive defense against sound-squatting candidates is complex, and existing solutions rely on manually curated
Externí odkaz:
http://arxiv.org/abs/2310.07005
Autor:
Boffa, Matteo, Valentim, Rodolfo Vieira, Vassio, Luca, Giordano, Danilo, Drago, Idilio, Mellia, Marco, Houidi, Zied Ben
Publikováno v:
Computers & Security, 2024, 103805, ISSN 0167-4048
The collection of security-related logs holds the key to understanding attack behaviors and diagnosing vulnerabilities. Still, their analysis remains a daunting challenge. Recently, Language Models (LMs) have demonstrated unmatched potential in under
Externí odkaz:
http://arxiv.org/abs/2307.08309
Web tracking through third-party cookies is considered a threat to users' privacy and is supposed to be abandoned in the near future. Recently, Google proposed the Topics API framework as a privacy-friendly alternative for behavioural advertising. Us
Externí odkaz:
http://arxiv.org/abs/2306.05094
The Reading&Machine project exploits the support of digitalization to increase the attractiveness of libraries and improve the users' experience. The project implements an application that helps the users in their decision-making process, providing r
Externí odkaz:
http://arxiv.org/abs/2303.11746