144 citations · 240 across the 10 of their papers we have counts for
10 papers
A latent space network model for dynamic neural latent embedding
Riccardo Rastelli, Shizhe Chen
We introduce a novel latent space network model for analyzing multivariate time series of neural spike-train data. The methodology is motivated by an experimental study in mice, wh…
Demystifying VEINS: A Reality Check Against Living Lab Experiments
Antonio Solida, Giovanni Gambigliani Zoccoli, Gaetano Orazio Cauchi +6
Safety applications in vehicle-to-everything communications and Cooperative Intelligent Transport Systems rely on reliable and timely message exchange, which in turn depends on acc…
RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs
Giovanni Gambigliani Zoccoli, Filip Valgimigli, Dario Stabili +1
This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems (C-ITS) that exploits multiple radio signals emitted by…
Finding (and exploiting) vulnerabilities on IP Cameras: the Tenda CP3 case study
Dario Stabili, Tobia Bocchi, Filip Valgimigli +1
Consumer IP cameras are now the most widely adopted solution for remote monitoring in various contexts, such as private homes or small offices. While the security of these devices…
HackCar: a test platform for attacks and defenses on a cost-contained automotive architecture
Dario Stabili, Filip Valgimigli, Edoardo Torrini +1
In this paper, we introduce the design of HackCar, a testing platform for replicating attacks and defenses on a generic automotive system without requiring access to a complete veh…
Problem space structural adversarial attacks for Network Intrusion Detection Systems based on Graph Neural Networks
Andrea Venturi, Dario Stabili, Mirco Marchetti
Machine Learning (ML) algorithms have become increasingly popular for supporting Network Intrusion Detection Systems (NIDS). Nevertheless, extensive research has shown their vulner…
Performance comparison of timing-based anomaly detectors for Controller Area Network: a reproducible study
Francesco Pollicino, Dario Stabili, Mirco Marchetti
This work presents an experimental evaluation of the detection performance of eight different algorithms for anomaly detection on the Controller Area Network (CAN) bus of modern ve…
Exploring the consequences of cyber attacks on Powertrain Cyber Physical Systems
Dario Stabili, Raffaele Romagnoli, Mirco Marchetti +2
This paper proposes a novel approach for the study of cyber-attacks against the powertrain of a generic vehicle. The proposed model is composed by a a generic Internal Combustion e…
Modeling Realistic Adversarial Attacks against Network Intrusion Detection Systems
Giovanni Apruzzese, Mauro Andreolini, Luca Ferretti +2
The incremental diffusion of machine learning algorithms in supporting cybersecurity is creating novel defensive opportunities but also new types of risks. Multiple researches have…
Hardening Random Forest Cyber Detectors Against Adversarial Attacks
Giovanni Apruzzese, Mauro Andreolini, Michele Colajanni +1
Machine learning algorithms are effective in several applications, but they are not as much successful when applied to intrusion detection in cyber security. Due to the high sensit…